A B C D E F G H I J K L M N O P Q R S T U V W X Y Z _

A

ABSOLUTE - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

Represents pruning with an absolute threshold.

ABSTRACT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

Ac - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Half of a sparse matrix representation of the constraints; this half contains the coefficients on the variables whose indexes appear in ZeroOneILPProblem.Av.

Accuracy - Class in edu.illinois.cs.cogcomp.lbjava.learn

Returns the accuracy of a discrete classifier with respect to the oracle as the fraction of examples for which its prediction was correct.

Accuracy() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Accuracy

Creates an Accuracy testing metric that does not print a table of results.

Accuracy(boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Accuracy

Creates an Accuracy testing metric that prints a table of results if requested.

action_obj - Variable in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Instance of action encapsulation class.

action_table() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Access to parse-action table.

AdaBoost - Class in edu.illinois.cs.cogcomp.lbjava.learn

Implementation of the AdaBoost binary classification learning algorithm.

AdaBoost() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Instantiates member variables.

AdaBoost(Learner) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Instantiates member variables.

AdaBoost(int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Instantiates member variables.

AdaBoost(Learner, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Instantiates member variables.

AdaBoost(AdaBoost.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Initializing constructor.

AdaBoost(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Instantiates member variables.

AdaBoost(String, Learner) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Instantiates member variables.

AdaBoost(String, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Instantiates member variables.

AdaBoost(String, Learner, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Instantiates member variables.

AdaBoost(String, AdaBoost.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Initializing constructor.

AdaBoost.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

A container for all of AdaBoost's configurable parameters.

AdaGrad - Class in edu.illinois.cs.cogcomp.lbjava.learn

AdaGrad - Adaptive Stochastic Gradient Method AdaGrad alters the update to adapt based on historical information, so that frequent occurring features in the gradients get small learning rates and infrequent features get higher ones.

AdaGrad() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Constructor The learning rate takes the default value, while the name of the classifier gets the empty string.

AdaGrad(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Constructor Sets the learning rate to the specified value, while the name of the classifier gets the empty string.

AdaGrad(AdaGrad.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Constructor Sets all member variables to their associated settings.

AdaGrad(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Constructor The learning rate takes the default value.

AdaGrad(String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Constructor Set desired learning rate

AdaGrad(String, AdaGrad.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Constructor Sets all member variables to their associated settings.

AdaGrad.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

A container for all of AdaGrad's configurable parameters.

add(FirstOrderConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConjunction

If the given constraint has the same type as this constraint, its terms are merged into this constraint; otherwise, it is added as a new term.

add(FirstOrderConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDisjunction

If the given constraint has the same type as this constraint, its terms are merged into this constraint; otherwise, it is added as a new term.

add(FirstOrderConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNAryConstraint

If the given constraint has the same type as this constraint, its terms are merged into this constraint; otherwise, it is added as a new term.

add(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

If the given constraint has the same type as this constraint, its terms are merged into this constraint; otherwise, it is added as a new term.

add(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

If the given constraint has the same type as this constraint, its terms are merged into this constraint; otherwise, it is added as a new term.

add(CatchClause) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchList

Adds another CatchClause to the end of the list.

add(ClassifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpressionList

Adds another ClassifierExpression to the end of the list.

add(Constant) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

Adds another Constant to the end of the list.

add(Declaration) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DeclarationList

Adds another Declaration to the end of the list.

add(Expression) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList

Adds another Expression to the end of the list.

add(ImportDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportList

Adds another ImportDeclaration to the end of the list.

add(ASTNode) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List.NodeListIterator

Inserts the specified node into the list.

add(Name) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NameList

Adds another Name to the end of the list.

add(Statement) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.StatementList

Adds another Statement to the end of the list.

add(SwitchGroup) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroupList

Adds another SwitchGroup to the end of the list.

add(SwitchLabel) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabelList

Adds another SwitchLabel to the end of the list.

add(LinkedChild) - Method in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

Adds the specified child to the end of the vector, informing the child of its parent and index and linking the child to its only neighbor (which was previously the last child in the vector).

add(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Adds the specified value on to the end of the vector, expanding its capacity as necessary.

addAll(CatchList) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchList

Adds all the CatchClauses in another CatchList to the end of this CatchList.

addAll(ClassifierExpressionList) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpressionList

Adds all the ClassifierExpressions in another ClassifierExpressionList to the end of this ClassifierExpressionList.

addAll(ConstantList) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

Adds all the Constants in another ConstantList to the end of this ConstantList.

addAll(DeclarationList) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DeclarationList

Adds all the Declarations in another DeclarationList to the end of this DeclarationList.

addAll(ExpressionList) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList

Adds all the Expressions in another ExpressionList to the end of this ExpressionList.

addAll(ImportList) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportList

Adds all the ImportDeclarations in another ImportList to the end of this ImportList.

addAll(NameList) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NameList

Adds all the Names in another NameList to the end of this NameList.

addAll(StatementList) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.StatementList

Adds all the Statements in another StatementList to the end of this StatementList.

addAll(SwitchGroupList) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroupList

Adds all the SwitchGroups in another SwitchGroupList to the end of this SwitchGroupList.

addAll(SwitchLabelList) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabelList

Adds all the SwitchLabels in another SwitchLabelList to the end of this SwitchLabelList.

addAll(FVector) - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Adds all the values in the given vector to the end of this vector, expanding its capacity as necessary.

addBooleanVariable(double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Adds a new Boolean variable (an integer variable constrained to take either the value 0 or the value 1) with the specified coefficient in the objective function to the problem.

addChild(SymbolTable) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Adds a child to this table.

addConstraint(int[], double[], int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Simply overrides ZeroOneILPProblem.addConstraint(int[],double[],int,double) so that it calls ZeroOneILPProblem.addConstraint(int[],double[],double) thereby ignoring the constraint's type.

addConstraint(FirstOrderConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Adds a constraint to the inference.

addConstraint(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Adds a typeless constraint to the problem.

addConstraint(int[], double[], int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Adds a new constraint of the specified type to the problem.

addDependor(String, String) - Static method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Adds an edge from dependency to dependor in the SemanticAnalysis.dependorGraph.

addDiscreteVariable(double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Adds a general, multi-valued discrete variable, which is implemented as a set of Boolean variables, one per value of the discrete variable, with exactly one of those variables set true at any given time.

addDiscreteVariable(Score[]) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Adds a general, multi-valued discrete variable, which is implemented as a set of Boolean variables, one per value of the discrete variable, with exactly one of those variables set true at any given time.

addEqualityConstraint(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Adds a new fixed constraint to the problem.

addEqualityConstraint(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Adds a new fixed constraint to the problem.

addFeature(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Adds a feature to the vector.

addFeatures(FeatureVector) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Adds all the features in another vector to this vector.

addGreaterThanConstraint(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Adds a new lower bounded constraint to the problem.

addGreaterThanConstraint(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Adds a new lower bounded constraint to the problem.

addImported(String) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Adds a name to the list of imported names in the top level table.

addIntegerVariable(double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

addLabel(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Adds a label to the vector.

addLabels(FeatureVector) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Adds all the features in another vector (but not the labels in that vector) to the labels of this vector.

addLessThanConstraint(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Adds a new upper bounded constraint to the problem.

addLessThanConstraint(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Adds a new upper bounded constraint to the problem.

addNull(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Adds a label to the set of "null" labels.

addRealVariable(double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

addVariables(VariableDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

Adds the declarations in the specified declaration statement to the declarations in this statement.

AFFECTED - Static variable in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Constant representing the "affected" revision status.

algorithm - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

(ø) A constructor for the inference algorithm to use.

allExamples - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

All the examples observed by this learner during training.

allExamples - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

The array of example vectors.

allLabels - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

The array of example labels

allowableValues() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Returns the array of allowable values that a feature returned by this classifier may take.

allowableValues() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ValueComparer

Returns the array of allowable values that a feature returned by this classifier may take.

allowableValues() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ParameterizedConstraint

Returns the array of allowable values that a feature returned by this classifier may take.

allowableValues - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

The label producing classifier's allowable values.

allowableValues() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Returns the array of allowable values that a feature returned by this classifier may take.

allowableValues - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

The label producing classifier's allowable values.

allowableValues() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Returns the array of allowable values that a feature returned by this classifier may take.

allowableValues - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

The label producing classifier's allowable values.

allowableValues() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Returns the array of allowable values that a feature returned by this classifier may take.

allowableValues - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

The label producing classifier's allowable values.

allowableValues() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Returns the array of allowable values that a feature returned by this classifier may take.

ALPHA - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

alpha - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(¬ø) The desired confidence level for cross validation's confidence interval output; argument to alpha, which can only be specified when cval is also specified.

ALPHA - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Value of the type variable

alpha - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Determines the parameter with which the confidence interval is calculated.

alpha - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Parameters associated with the trained copies of the weak learner.

alpha - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Sigmoid

The user-specified constant described above.

alpha - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Softmax

The user-specified constant described above.

alphaClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Counts the number of alpha clauses, for error detection.

AND - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

AND - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

AND_ASSIGN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

ANDAND - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

ANDEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

anonymousClassifier(String) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Creates a new anonymous classifier name.

anonymousFiles(Name) - Method in class edu.illinois.cs.cogcomp.lbjava.Clean

Adds files generated for anonymous classes associated with a particular named classifier to the remove list.

append(String) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Appends the encoding of the given string onto the existing encoding in this object.

append(String[]) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Appends the encodings of all the given strings onto the existing encoding in this object.

append(ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Appends the string represented by the given byte string onto the existing content in this object.

append(ByteString[]) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Appends the strings represented by the given byte strings onto the existing content in this object.

Argument - Class in edu.illinois.cs.cogcomp.lbjava.IR

An "argument" is the specification of a classifier's input parameter.

Argument(Type, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Argument

Initializing constructor.

Argument(Type, String, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Argument

Initializing constructor.

argument - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.CatchClause

(¬ø) The catch's input specification

argument - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

(¬ø) The input specification of the classifier.

argument - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpression

Specification of the classifier's input.

argument - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintDeclaration

(¬ø) The input specification of the constraint.

argument - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.Clause

The argument of the clause.

argument - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.HeadFinder

(¬ø) Input specification of the head finder method.

argument - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

The argument of the clause.

argument - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.QuantifiedConstraintExpression

(¬ø) The variable specified by this argument is set to each of the objects from the collection in turn and used throughout the quantified constraint.

ArgumentReplacer - Class in edu.illinois.cs.cogcomp.lbjava.infer

Anonymous inner classes extending this class are instantiated by the code generated by the LBJava compiler when creating FirstOrderConstraint representations.

ArgumentReplacer(Object[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ArgumentReplacer

Initializing constructor.

arguments - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

(¬ø) The argument expressions passed to the method.

array - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SubscriptVariable

(¬ø) The expression describing the array to be accessed.

ArrayCreationExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents an expression creating an array.

ArrayCreationExpression(Type, ExpressionList, int, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ArrayCreationExpression

Initializing constructor.

ArrayCreationExpression(Type, int, ArrayInitializer, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ArrayCreationExpression

Initializing constructor.

ArrayFileParser - Class in edu.illinois.cs.cogcomp.lbjava.parse

This parser returns an array of arrays representing each example.

ArrayFileParser(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

Initializes the parser with a file name assuming the input stream is not zipped.

ArrayFileParser(String, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

Initializes the parser with a file name, specifying whether the data is zipped.

ArrayFileParser(byte[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

Initializes the parser with a data array assuming the input stream is not zipped.

ArrayFileParser(byte[], boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

Initializes the parser with a data array, specifying whether the data is zipped.

arrayIndex - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

The feature's index in the returned array it is contained in.

arrayIndex - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

The feature's index in the returned array it is contained in.

arrayIndex - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

The feature's index in the returned array it is contained in.

arrayIndex - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

The feature's index in the returned array it is contained in.

ArrayInitializer - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents those expressions that can be used to set all the values in an array.

ArrayInitializer() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ArrayInitializer

Default constructor.

ArrayInitializer(int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ArrayInitializer

Initializing constructor.

ArrayInitializer(ExpressionList, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ArrayInitializer

Full constructor.

arrayLength - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

The size of the returned array this feature is contained in.

arrayLength - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

The size of the returned array this feature is contained in.

arrayLength - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

The size of the returned array this feature is contained in.

arrayLength - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

The size of the returned array this feature is contained in.

ArrayParser - Class in edu.illinois.cs.cogcomp.lbjava.parse

This parser returns the example objects in an array one at a time.

ArrayParser() - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.ArrayParser

Initializes the parser with an empty example array.

ArrayParser(Object[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.ArrayParser

Creates the parser with the supplied example array.

ArrayType - Class in edu.illinois.cs.cogcomp.lbjava.IR

Class for representing array types.

ArrayType(Type) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ArrayType

Initializing constructor.

ARROW - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

ARROW - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

asciiTableFormat(int, int, int, int, String[], String[], Double[][], int[], int[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table.

ASSERT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

AssertStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents an assertion statement.

AssertStatement(Expression, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.AssertStatement

Initializing constructor.

AssertStatement(Expression, Expression, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.AssertStatement

Full constructor.

ASSIGN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

Assignment - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents the assignment of a value to a storage location.

Assignment(Operator, Expression, Expression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Assignment

Initializing constructor.

AST - Class in edu.illinois.cs.cogcomp.lbjava.IR

The root node of LBJava's AST.

AST(DeclarationList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.AST

Initializes just the statement list.

AST(ImportList, DeclarationList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.AST

Initializes both lists.

AST(PackageDeclaration, DeclarationList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.AST

Initializes package declaration and statement list.

AST(PackageDeclaration, ImportList, DeclarationList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.AST

Initializes all member variables.

AST(PackageDeclaration, ImportList, DeclarationList, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.AST

Full constructor.

ast - Variable in class edu.illinois.cs.cogcomp.lbjava.Pass

Stores the same thing as root, but this variable is declared as AST .

ASTNode - Class in edu.illinois.cs.cogcomp.lbjava.IR

Abstract node class that every AST node extends.

ASTNode() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ASTNode

Default constructor.

ASTNode(int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ASTNode

Initializing constructor.

ASTNodeIterator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Used to iterate though the children of an AST node.

ASTNodeIterator() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ASTNodeIterator

Initializes index, but not children.

ASTNodeIterator(int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ASTNodeIterator

The children array will have the specified length.

AT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

ATLEAST - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

AtLeastQuantifier - Class in edu.illinois.cs.cogcomp.lbjava.infer

An "at least" quantifier states that the constraint must hold for at least m of the objects in the collection.

AtLeastQuantifier(String, Collection, FirstOrderConstraint, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.AtLeastQuantifier

Initializing constructor.

AtLeastQuantifier(String, Collection, FirstOrderConstraint, int, QuantifierArgumentReplacer) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.AtLeastQuantifier

This constructor specifies a variable setter for when this quantifier is itself quantified.

AtLeastQuantifierExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

An "at least" quantifier has the form: atleast expression of argument in (expression) constraint-expression where the first expression must evaluate to an int, the second expression must evaluate to a Collection, and the "at least" quantifier expression is sastisfied iff when taking settings of argument from the Collection, constraint-expression is satisfied at least as many times as the integer the first expression evaluates to.

AtLeastQuantifierExpression(int, int, Expression, Argument, Expression, ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.AtLeastQuantifierExpression

Full constructor.

AtLeastQuantifierExpression(TokenValue, Expression, Argument, Expression, ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.AtLeastQuantifierExpression

Parser's constructor.

ATMOST - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

AtMostQuantifier - Class in edu.illinois.cs.cogcomp.lbjava.infer

An "at most" quantifier states that the constraint must hold for no more than m of the objects in the collection.

AtMostQuantifier(String, Collection, FirstOrderConstraint, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.AtMostQuantifier

Initializing constructor.

AtMostQuantifier(String, Collection, FirstOrderConstraint, int, QuantifierArgumentReplacer) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.AtMostQuantifier

This constructor specifies a variable setter for when this quantifier is itself quantified.

AtMostQuantifierExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

An "at most" quantifier has the form: atmost expression of argument in (expression) constraint-expression where the first expression must evaluate to an int, the second expression must evaluate to a Collection, and the "at most" quantifier expression is sastisfied iff when taking settings of argument from the Collection, constraint-expression is satisfied at most as many times as the integer the first expression evaluates to.

AtMostQuantifierExpression(int, int, Expression, Argument, Expression, ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.AtMostQuantifierExpression

Full constructor.

AtMostQuantifierExpression(TokenValue, Expression, Argument, Expression, ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.AtMostQuantifierExpression

Parser's constructor.

attributeInfo - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Information about the features this learner takes as input is parsed from an attribute string and stored here.

attributeString - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

A string representation of the return type information for each feature.

attributeString - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

A string encoding of the attributes used by this learner.

attributeString - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper.Parameters

A string encoding of the return types of each of the feature extractors in use; default WekaWrapper.defaultAttributeString.

Av - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Half of a sparse matrix representation of the constraints; this half contains the variable indexes corresponding to the coefficients in ZeroOneILPProblem.Ac.

available() - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexInputStream

Returns the number of bytes that can be read (or skipped over) from this input stream without blocking by the next caller of a method for this input stream.

averagedBias - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Keeps the extra information necessary to compute the averaged bias.

averagedWeights - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Together with SparseWeightVector.weights, this vector provides enough information to reconstruct the average of all weight vectors arrived at during the course of learning.

AveragedWeightVector() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Simply instantiates the weight vectors.

AveragedWeightVector(double[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Simply initializes the weight vectors.

AveragedWeightVector(DVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Simply initializes the weight vectors.

awv - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Holds the same reference as LinearThresholdUnit.weightVector casted to SparseAveragedPerceptron.AveragedWeightVector.

B

BalasHook - Class in edu.illinois.cs.cogcomp.lbjava.infer

This ILPSolver implements Egon Balas' zero-one ILP solving algorithm.

BalasHook() - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Default constructor.

BalasHook(int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Creates a new ILP solver with the specified verbosity.

BalasHook(boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Creates a new ILP solver that halts at the first feasible solution found, if the parameter to this constructor is true.

BalasHook(boolean, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Creates a new ILP solver that halts at the first feasible solution found, if the first parameter to this constructor is true.

BalasHook(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Creates a new ILP solver with the problem represented in the named file loaded and ready to solve.

BalasHook(String, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Creates a new ILP solver with the problem represented in the named file loaded and ready to solve.

BalasHook(String, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Creates a new ILP solver with the problem represented in the named file loaded and ready to solve.

BalasHook(String, boolean, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Creates a new ILP solver with the problem represented in the named file loaded and ready to solve.

BANGCOLON - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

baseClassifier - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Stores the instance of the WEKA classifier which we are training; default is weka.classifiers.bayes.NaiveBayes.

baseClassifier - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper.Parameters

Stores the instance of the WEKA classifier which we are training; default WekaWrapper.defaultBaseClassifier.

baseLearner - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Instances of this learning algorithm will be multiplexed; default null.

baseLearner - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner.Parameters

Instances of this learning algorithm will be multiplexed; default null.

baseLTU - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

The underlying algorithm used to learn each class separately as a binary classifier; default SparseNetworkLearner.defaultBaseLTU.

baseLTU - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner.Parameters

The underlying algorithm used to learn each class separately as a binary classifier; default SparseNetworkLearner.defaultBaseLTU.

BatchTrainer - Class in edu.illinois.cs.cogcomp.lbjava.learn

Use this class to batch train a Learner.

BatchTrainer(Learner, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Creates a new trainer that doesn't produce status messages.

BatchTrainer(Learner, String, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Creates a new trainer that produces status messages.

BatchTrainer(Learner, String, int, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Creates a new trainer that produces status messages with the specified indentation spacing for status messages.

BatchTrainer(Learner, String, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Creates a new trainer that doesn't produce status messages.

BatchTrainer(Learner, String, boolean, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Creates a new trainer that produces status messages.

BatchTrainer(Learner, String, boolean, int, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Creates a new trainer that produces status messages with the specified indentation spacing for status messages.

BatchTrainer(Learner, Parser) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Creates a new trainer that doesn't produce status messages.

BatchTrainer(Learner, Parser, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Creates a new trainer that produces status messages.

BatchTrainer(Learner, Parser, int, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Creates a new trainer that produces status messages with the specified indentation spacing for status messages.

BatchTrainer.DoneWithRound - Interface in edu.illinois.cs.cogcomp.lbjava.learn

Provides access to a hook into BatchTrainer.train(int) so that additional processing can be performed at the end of each round.

beta - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

The user supplied learning algorithm parameter; default BinaryMIRA.defaultBeta.

beta - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA.Parameters

The user supplied learning algorithm parameter; default BinaryMIRA.defaultBeta.

beta - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

The rate at which weights are demoted; default equal to 1 / LinearThresholdUnit.learningRate.

beta - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow.Parameters

The rate at which weights are demoted; default equal to 1 / LinearThresholdUnit.learningRate.

bias - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedRandomWeightVector

The current bias weight.

bias - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

The current bias weight.

bias - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

The bias is stored here rather than as an element of the weight vector.

bias - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

The bias is stored here rather than as an element of the weight vector.

bias - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

If SupportVectorMachine.bias >= 0, an instance vector x becomes [x; bias]; otherwise, if SupportVectorMachine.bias < 0, no bias term is added.

bias - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine.Parameters

If SupportVectorMachine.bias >= 0, an instance vector x becomes [x; bias]; otherwise, if SupportVectorMachine.bias < 0, no bias term is added.

BiasedRandomWeightVector - Class in edu.illinois.cs.cogcomp.lbjava.learn

Same as the RandomWeightVector class that it extends, except that this vector also contains a bias term (also initialized randomly) which is added to every dot product and affected by every vector addition operation.

BiasedRandomWeightVector() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BiasedRandomWeightVector

Instantiates this biased vector with a random bias.

BiasedRandomWeightVector(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BiasedRandomWeightVector

Sets the specified standard deviation and a random bias.

BiasedWeightVector - Class in edu.illinois.cs.cogcomp.lbjava.learn

Same as the SparseWeightVector class that it extends, except that this vector also contains a bias term which is added to every dot product and affected by every vector addition operation.

BiasedWeightVector() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

Instantiates this biased vector with default parameter values.

BiasedWeightVector(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

Instantiates this biased vector with the specified initial bias.

biasFeatures - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

The number of bias features; there are either 0 or 1 of them.

BinaryConstraintExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents a constraint expression involving a binary operator.

BinaryConstraintExpression(Operator, ConstraintExpression, ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.BinaryConstraintExpression

Initializing constructor.

BinaryExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents an expression involving a binary operator.

BinaryExpression(Operator, Expression, Expression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.BinaryExpression

Initializing constructor.

BinaryMIRA - Class in edu.illinois.cs.cogcomp.lbjava.learn

The Binary MIRA learning algorithm implementation.

BinaryMIRA() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

The learning rate and beta take default values while the name of the classifier takes the empty string.

BinaryMIRA(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Sets the learning rate to the specified value, and beta to the default, while the name of the classifier takes the empty string.

BinaryMIRA(double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Sets the learning rate and beta to the specified values, while the name of the classifier takes the empty string.

BinaryMIRA(double, double, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Sets the learning rate, beta and the weight vector to the specified values.

BinaryMIRA(BinaryMIRA.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Initializing constructor.

BinaryMIRA(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Sets the name of the classifier to the specified value, while the learning rate and beta take default values.

BinaryMIRA(String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Sets the name of the classifier and learning rate to the specified values, while beta takes the default value.

BinaryMIRA(String, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Sets the name of the classifier, the learning rate and beta to the specified values.

BinaryMIRA(String, double, double, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Sets the name of the classifier, the learning rate, beta and the weight vector to the specified values.

BinaryMIRA(String, BinaryMIRA.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Initializing constructor.

BinaryMIRA.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of BinaryMIRA's configurable parameters.

BITWISE_AND - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

BITWISE_NOT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

BITWISE_NOT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

BITWISE_OR - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

Block - Class in edu.illinois.cs.cogcomp.lbjava.IR

A block is just a list of statements in between curly braces.

Block(int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Block

Initializing constructor.

Block(StatementList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Block

Initializing constructor.

block - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.CatchClause

(¬ø) The code to execute when an exception is caught.

block - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchStatement

(¬ø) The various code blocks that are executed depending on the expression's value.

block - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SynchronizedStatement

(¬ø) The code to execute while the data is protected.

block - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.TryStatement

(¬ø) The code to look for exceptions in.

body - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.CodedClassifier

(¬ø) Statements making up the body of the hard-coded classifier.

body - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintDeclaration

(¬ø) Statements making up the body of the constraint.

body - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

(¬ø) The body of the loop.

body - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.HeadFinder

(¬ø) Body of the head finder method.

body - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.WhileStatement

(¬ø) The body of the loop.

BOOLEAN - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

BOOLEAN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Value of the type variable.

BooleanValues - Static variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

Convient access to a common allowable value set.

boundConstant - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifierArgumentReplacer

This flag is set if the bound parameter of an AtLeastQuantifier or an AtMostQuantifier is not quantified.

bounds - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

The vector of constraint bounds.

boundsCheck(int) - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Throws an exception when the specified index is negative.

boundTypes - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Contains the types of the constraints.

boundTypeSymbols - Static variable in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Maps from the three constraint types to their operator symbols.

BREAK - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

BreakStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a break statement.

BreakStatement(String, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.BreakStatement

Full constructor.

buffer - Variable in class edu.illinois.cs.cogcomp.lbjava.io.ChannelOutputStream

Holds data until it is written.

BYTE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

BYTE - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Value of the type variable.

byteOffset - Variable in class edu.illinois.cs.cogcomp.lbjava.frontend.TokenValue

The byte offset in the file at which the token is found in the source file.

byteOffset - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNode

The byte offset from the beginning of the source file at which the source code represented by this node is found.

byteOffset - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

The byte offset at which the learner appeared.

ByteString - Class in edu.illinois.cs.cogcomp.lbjava.util

Represents a String by directly storing an encoding of that String in an array of bytes.

ByteString(boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.ByteString

For internal use only.

ByteString() - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Creates an empty byte string.

ByteString(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Creates a byte string by using the default encoding to encode the specified string.

ByteString(String, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Creates a byte string by using the specified encoding to encode the specified string.

ByteString(ByteString, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Creates a byte string with the given encoding, which may involve converting the specified byte string's contents if the encodings differ.

C

C - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

The cost parameter C; default SupportVectorMachine.defaultC

C - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine.Parameters

The cost parameter C; default SupportVectorMachine.defaultC

CACHED - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

CACHEDIN - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

CACHEDINMAP - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

cacheIn - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

(ø) The expression representing the field to cache this classifier's result in.

cacheIn - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpression

(ø) The expression representing the field to cache this classifier's result in.

canAddErrorsAndWarnings - Static variable in class edu.illinois.cs.cogcomp.lbjava.Pass

A global flag controlling whether or not errors and warnings can currently be added.

candidates - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

The number of candidate examples when a global object is passed here.

CASE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

CastExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

Representation of an expression that casts a value to another type.

CastExpression(Type, Expression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.CastExpression

Initializing constructor.

castType - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierCastExpression

(¬ø) The return type used to cast.

CATCH - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

CatchClause - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a catch clause on a try statement.

CatchClause(Argument, Block, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.CatchClause

Full constructor.

CatchList - Class in edu.illinois.cs.cogcomp.lbjava.IR

Currently, this is just a wrapper class for LinkedList.

CatchList() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.CatchList

Default constructor.

CatchList(CatchClause) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.CatchList

Initializing constructor.

catchList - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.TryStatement

(¬ø) A list of clauses for catching exceptions, if any.

CatchList.CatchListIterator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Used to iterate though the children of a list of AST nodes.

CatchListIterator() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.CatchList.CatchListIterator

center(String, int) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Returns a space-padded string of at least the specified width such that the argument string is centered within the returned string.

channel - Variable in class edu.illinois.cs.cogcomp.lbjava.io.ChannelOutputStream

The channel where the data will be written.

ChannelOutputStream - Class in edu.illinois.cs.cogcomp.lbjava.io

This class implements an output stream that buffers output in a directly allocated ByteBuffer before writing it to a channel.

ChannelOutputStream(WritableByteChannel) - Constructor for class edu.illinois.cs.cogcomp.lbjava.io.ChannelOutputStream

Creates the stream from the channel where the data will be written.

ChannelOutputStream(WritableByteChannel, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.io.ChannelOutputStream

Creates the stream from the channel where the data will be written and a buffer size.

CHAR - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

CHAR - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Value of the type variable.

checkDiscreteValues - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

The SemanticAnalysis pass will let this LearningClassifierExpression know if the features it generates need to be checked for appropriateness in the context of the enclosing ClassifierAssignment by setting this flag.

ChildLexicon - Class in edu.illinois.cs.cogcomp.lbjava.learn

Instances of this class are intended to store features that are children of other features and which do not correspond to their own weights in any learner's weight vector.

ChildLexicon() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Creates an empty lexicon.

ChildLexicon(Lexicon) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Creates an empty lexicon.

ChildLexicon(Lexicon, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Creates an empty lexicon with the given encoding.

childLexiconLookup(ChildLexicon, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Does a feature-type-specific lookup of this feature in the given ChildLexicon.

childLexiconLookup(ChildLexicon, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Does a feature-type-specific lookup of this feature in the given ChildLexicon.

childLexiconLookup(ChildLexicon, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Does a feature-type-specific lookup of this feature in the given ChildLexicon.

childLexiconLookup(ChildLexicon, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Does a feature-type-specific lookup of this feature in the given ChildLexicon.

childLexiconLookup(ChildLexicon, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Does a feature-type-specific lookup of this feature in the given ChildLexicon.

childLexiconLookup(Feature, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Updates the counts in ChildLexicon.parents for the children of f.

childLexiconLookup(DiscreteConjunctiveFeature, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Updates the counts in ChildLexicon.parents for the children of f.

childLexiconLookup(RealConjunctiveFeature, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Updates the counts in ChildLexicon.parents for the children of f.

childLexiconLookup(DiscreteReferrer, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Updates the counts in ChildLexicon.parents for the children of f.

childLexiconLookup(RealReferrer, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Updates the counts in ChildLexicon.parents for the children of f.

children - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNAryConstraint

The children of the operator.

children - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

The children are stored in an array in this class.

children - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNAryConstraint

The children of the operator.

children - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNodeIterator

The nodes iterated through by this iterator.

children - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

The linked vector is simply represented as a vector of children.

ChildrenFromVectors - Class in edu.illinois.cs.cogcomp.lbjava.parse

Use this parser in conjunction with another parser that returns LinkedVectors, and this parser will return their LinkedChildren.

ChildrenFromVectors(Parser) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.ChildrenFromVectors

Creates the parser.

CLASS - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

classDir - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

The directory into which class files, model files, etc are written.

classDirectory - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

The directory in which Javac will place class files (with subdirectories mimicing the package name included).

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classEquivalent(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Some features are functionally equivalent, differing only in the encoding of their values; this method will return true iff the class of this feature and f are different, but they differ only because they encode their values differently.

classForName(ClassifierName) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Attempts to locate the named class in the current package and any imported packages.

classForName(String) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Attempts to locate the named class in the current package and any imported packages.

classForName(Name) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Attempts to locate the named class in the current package and any imported packages.

Classifier - Class in edu.illinois.cs.cogcomp.lbjava.classify

Objects of this class represent functions that make some multi-valued decision about an object.

Classifier() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Does nothing.

Classifier(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Initializing constructor.

classifier - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

The classifier being applied.

classifier - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceInvocation

(¬ø) The name of the argument learning classifier.

ClassifierAssignment - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents the assignment of a classifier expression to a method signature.

ClassifierAssignment(String, ClassifierReturnType, Name, Argument, ClassifierExpression, Name, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

Full constructor.

ClassifierAssignment(ClassifierReturnType, TokenValue, Argument, ClassifierExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

Parser's constructor.

ClassifierAssignment(ClassifierReturnType, TokenValue, Argument, ClassifierExpression, Name) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

Parser's constructor.

ClassifierAssignment(ClassifierReturnType, TokenValue, Argument, ClassifierExpression, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

Parser's constructor.

ClassifierAssignment(ClassifierReturnType, TokenValue, Argument, ClassifierExpression, Name, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

Parser's constructor.

ClassifierCastExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents a classifier cast expression.

ClassifierCastExpression(ClassifierReturnType, ClassifierExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierCastExpression

Initializing constructor.

ClassifierCSE - Class in edu.illinois.cs.cogcomp.lbjava

This pass performs common subexpression elimination on classifier expressions except for ClassifierNames and LearningClassifierExpressions.

ClassifierCSE(AST) - Constructor for class edu.illinois.cs.cogcomp.lbjava.ClassifierCSE

Instantiates a pass that runs on an entire AST.

ClassifierExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

Abstract classifier expression class.

ClassifierExpressionList - Class in edu.illinois.cs.cogcomp.lbjava.IR

Currently, this is just a wrapper class for LinkedList.

ClassifierExpressionList() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpressionList

Default constructor.

ClassifierExpressionList(ClassifierExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpressionList

Initializing constructor.

ClassifierExpressionList.ClassifierExpressionListIterator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Used to iterate though the children of a list of AST nodes.

ClassifierExpressionListIterator() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpressionList.ClassifierExpressionListIterator

ClassifierName - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents identifiers that name classifiers.

ClassifierName(Name) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierName

Full constructor.

ClassifierName(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierName

Takes a fully specified name (eg java.lang.String) as input.

ClassifierName(String, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierName

Takes a fully specified name (eg java.lang.String) as input.

ClassifierReturnType - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents the return type of a hard-coded classifier.

ClassifierReturnType(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

This constructor parses the name of a classifier return type as it would appear in the source, assuming value lists have been omitted.

ClassifierReturnType(String, ConstantList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

This constructor parses the name of a classifier return type as it would appear in the source, assuming value lists have been omitted.

ClassifierReturnType(int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Default constructor.

ClassifierReturnType(int, ConstantList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Default constructor.

ClassifierReturnType(int, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Initializing constructor.

ClassifierReturnType(int, ConstantList, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Full constructor.

ClassifierType - Class in edu.illinois.cs.cogcomp.lbjava.IR

A classifier's type is defined by what it takes as input and what it returns as output, but it is distinguished only by what it takes as input.

ClassifierType(Type, ClassifierReturnType, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

Initializing constructor.

classify(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

This method makes one or more decisions about a single object, returning those decisions as Features in a vector.

classify(Object[]) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Use this method to make a batch of classification decisions about several objects.

classify(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVectorReturner

This method makes one or more decisions about a single object, returning those decisions as Features in a vector.

classify(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.LabelVectorReturner

This method makes one or more decisions about a single object, returning those decisions as Features in a vector.

classify(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.MultiValueComparer

Returns a Boolean feature (with value "true" or "false") indicating whether the output of ValueComparer.labeler applied to the argument object contained the feature value referenced by ValueComparer.value.

classify(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ValueComparer

Returns a Boolean feature (with value "true" or "false") representing the equality of the output of ValueComparer.labeler applied to the argument object and ValueComparer.value.

classify(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ParameterizedConstraint

This method makes one or more decisions about a single object, returning those decisions as Features in a vector.

classify(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

This method uses the trained parameters to make a binary decision about an example object.

classify(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Simply computes the dot product of the weight vector and the feature vector extracted from the example object.

classify(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

This method makes one or more decisions about a single object, returning those decisions as Features in a vector.

classify(FeatureVector) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

This method makes one or more decisions about a single feature vector, returning those decisions as Features in a vector.

classify(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

This method makes one or more decisions about a single object, returning those decisions as Features in a vector.

classify(FeatureVector[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Use this method to make a batch of classification decisions about several objects.

classify(Object[][]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Use this method to make a batch of classification decisions about several examples.

classify(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

The default evaluation method simply computes the score for the example and returns a DiscretePrimitiveStringFeature set to either the second value from the label classifier's array of allowable values if the score is greater than or equal to LinearThresholdUnit.threshold or the first otherwise.

classify(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner

Returns a separate feature for each LinearThresholdUnit whose score on the example object exceeds the threshold.

classify(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

This method performs the multiplexing and returns the output of the selected Learner.

classify(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Prediction value counts and feature counts given a particular prediction value are used to select the most likely prediction value.

classify(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

This implementation uses a winner-take-all comparison of the individual weight vectors' dot products.

classify(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

This implementation uses a winner-take-all comparison of the outputs from the individual linear threshold units' score methods.

classify(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Simply computes the dot product of the weight vector and the feature vector extracted from the example object.

classify(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Evaluates the given example using liblinear's prediction method.

classify(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

This method makes one or more decisions about a single object, returning those decisions as Features in a vector.

classPackageDirectory - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

The directory in which class files should be written, not including the subdirectory structure that mimics the package.

classPath - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

The directory in which to search for source files.

ClassUtils - Class in edu.illinois.cs.cogcomp.lbjava.util

Utility methods for retrieving various classes that are part of the LBJava class hierarchy by name.

ClassUtils() - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Clause(int, ASTNode) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.Clause

Full constructor.

Clause(int, ASTNode) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Initializing constructor.

Clause(int, ASTNode, Expression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Full constructor.

Clause(int, Constant, Constant, Constant) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

A constructor with 3 Constant parameters, used for the prune clause.

Clause(int, Name, Block) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

A constructor for a with clause with a parameter setting block.

Clause(int, ASTNode, Expression, Block, Constant, FoldParser.SplitPolicy, Constant, Constant, Constant, Constant, Constant) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

This constructor is only called by LearningClassifierExpression.Clause.clone().

Clean - Class in edu.illinois.cs.cogcomp.lbjava

To be run after SemanticAnalysis, this pass compiles the list of files created by the LBJava compiler and removes them.

Clean(AST) - Constructor for class edu.illinois.cs.cogcomp.lbjava.Clean

Instantiates a pass that runs on an entire AST.

clean - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

This flag is set to true if cleaning has been enabled on the command line.

clear() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Removes all elements from both FeatureVector.features and FeatureVector.labels.

clear() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedRandomWeightVector

Empties the weight map and resets the random number generator.

clear() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

Empties the weight map.

clear() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Clears the data structures associated with this instance.

clear() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Clears the data structures associated with this instance.

clear() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

Empties the weight map and resets the random number generator.

clear() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Empties the weight map.

clearLabels() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Removes all elements from just the FeatureVector.labels list.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

This method returns a shallow clone.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Returns a shallow clone of this Feature.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns a shallow clone of this vector; the vectors are cloned, but their elements aren't.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Score

Produces a deep copy of this object.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ScoreSet

Produces a deep copy of this object.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderVariable

This method returns a shallow clone.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

This method returns a shallow clone.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

This method returns a shallow clone.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNAryConstraint

This method returns a shallow clone.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Argument

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayCreationExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayInitializer

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayType

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AssertStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Assignment

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AST

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNode

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AtLeastQuantifierExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AtMostQuantifierExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryConstraintExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Block

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BreakStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CastExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchClause

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchList

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierCastExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpressionList

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierName

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Creates a new object with the same primitive data.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CodedClassifier

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CompositeGenerator

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conditional

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conjunction

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Constant

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintDeclaration

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintInvocation

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintStatementExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintType

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ContinueStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DeclarationList

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DoStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.EmptyStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExistentialQuantifierExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.FieldAccess

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.IfStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportDeclaration

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportList

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.IncrementExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.Clause

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.HeadFinder

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.NormalizerDeclaration

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceInvocation

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InstanceCreationExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InstanceofExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LabeledStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Name

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NameList

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NegatedConstraintExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NormalizerType

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PackageDeclaration

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Creates a new object with the same primitive data.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReferenceType

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReturnStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.StatementList

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SubscriptVariable

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroup

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroupList

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabel

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabelList

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SynchronizedStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ThrowStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.TryStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.UnaryExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.UniversalQuantifierExpression

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.WhileStatement

Creates a new object with the same primitive data, and recursively creates new member data objects as well.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns a deep (enough) clone of this learner.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Returns a deep clone of this lexicon implemented as a HashMap.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Returns a deep clone of this learning algorithm.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Returns a deep clone of this learning algorithm.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Returns a deep clone of this learning algorithm.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Count

This method returns a shallow clone.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Returns a copy of this NaiveBayesVector.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Returns a copy of this AveragedWeightVector.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Returns a deep clone of this learning algorithm.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Returns a deep clone of this learning algorithm.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Returns a deep clone of this learning algorithm.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Returns a copy of this SparseWeightVector in which the SparseWeightVector.weights variable has been cloned deeply.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Returns a deep clone of this learning algorithm.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedChild

Returns a shallow clone of this object.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

Returns a clone of this object that is deep in the sense that all of the children objects are cloned.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Returns a shallow copy of this string.

clone() - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Returns a shallow clone of this vector; the vector itself is cloned, but the element objects aren't.

close() - Method in class edu.illinois.cs.cogcomp.lbjava.io.ChannelOutputStream

Flushes the ChannelOutputStream.buffer and closes the ChannelOutputStream.channel.

close() - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexInputStream

Closes this input stream and releases any system resources associated with the stream.

close() - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexOutputStream

Closes this output stream and releases any system resources associated with this stream.

close() - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexStringInputStream

Closes this input stream and releases any system resources associated with the stream.

close() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

Frees any resources this parser may be holding.

close() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayParser

Frees any resources this parser may be holding.

close() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.ChildrenFromVectors

Frees any resources this parser may be holding.

close() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Frees any resources this parser may be holding.

close() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.LineByLine

Frees any resources this parser may be holding.

close() - Method in interface edu.illinois.cs.cogcomp.lbjava.parse.Parser

Frees any resources this parser may be holding.

CNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Produces a new, logically simplified version of this constraint in conjunctive normal form (CNF).

CNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Produces a new, logically simplified version of this constraint in conjunctive normal form (CNF).

CNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Produces a new, logically simplified version of this constraint in conjunctive normal form (CNF).

CNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Produces a new, logically simplified version of this constraint in conjunctive normal form (CNF).

CNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Produces a new, logically simplified version of this constraint in conjunctive normal form (CNF).

CNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Produces a new, logically simplified version of this constraint in conjunctive normal form (CNF).

CNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Produces a new, logically simplified version of this constraint in conjunctive normal form (CNF).

CNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Produces a new, logically simplified version of this constraint in conjunctive normal form (CNF).

CNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Produces a new, logically simplified version of this constraint in conjunctive normal form (CNF).

CodedClassifier - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a hard-coded classifier definition.

CodedClassifier(Block) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.CodedClassifier

Full constructor.

CodeGenerator - Interface in edu.illinois.cs.cogcomp.lbjava

All IR classes for which code is generated implement this interface.

collection - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.Quantifier

The collection of objects to iterate over.

collection - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.QuantifiedConstraintExpression

(¬ø) The objects to iterate through; it must evaluate to a Java Collection.

collectionConstant - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifierArgumentReplacer

This flag is set if the collection of the quantifier is not quantified.

collectionIsQuantified - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.QuantifiedConstraintExpression

Filled in by SemanticAnalysis, this flag is set if collection contains any quantified variables.

COLON - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

COLONCOLON - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

columns() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Returns the number of variables in the ILP problem.

COMMA - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

comment - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpression

(ø) The text of a Javadoc comment that may be associated with this classifier.

comment - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Declaration

(ø) The text of a Javadoc comment that may appear before the declaration.

compareNameStrings(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Compares only the run-time types, packages, classifier names, and identifiers of the features.

compareNameStrings(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Compares only the run-time types, packages, classifier names, and identifiers of the features.

compareNameStrings(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Compares only the run-time types, packages, classifier names, and identifiers of the features.

compareNameStrings(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Compares only the run-time types, packages, classifier names, and identifiers of the features.

compareNameStrings(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Compares only the run-time types, packages, classifier names, and identifiers of the features.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Used to sort features into an order that is convenient both to page through and for the lexicon to read off disk.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Score

This method is implemented so that a collection of Scores will be sorted first by value and then by score.

compareTo(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

If the argument object is a byte string, this object's byte array and the argument object's byte array are compared lexicographically.

components - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.CompositeGenerator

(¬ø) The list of classifiers composing this classifier.

CompositeGenerator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a generator composed from several other classifiers.

CompositeGenerator(ClassifierExpressionList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.CompositeGenerator

Full constructor.

CompositeGenerator(ClassifierExpression, ClassifierExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.CompositeGenerator

Parser's constructor.

compressAndPrint(StringBuffer, PrintStream) - Static method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Compress the textual representation of an ASTNode, convert to ASCII hexadecimal, and write the result to the specified stream.

compute() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.InvocationArgumentReplacer

Computes the value of the constraint invocation's parameter.

computeLearningRate(int[], double[], double, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Computes the learning rate for this example.

computeLearningRate(int[], double[], double, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Computes the value of the LinearThresholdUnit.learningRate variable if needed and returns the value.

computeLearningRate(int[], double[], double, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Computes the value of the learning rate for this example.

computeLearningRate(int[], double[], double, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Returns the learning rate, which is LinearThresholdUnit.learningRate (alpha) if it is a positive example, and SparseWinnow.beta if it is a negative example.

concurrentTraining - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

This flag is set if concurrent training has been enabled.

condition - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.AssertStatement

(¬ø) The condition that must hold; otherwise, an assertion error is generated.

condition - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Conditional

(¬ø) The condition of the conditional expression.

condition - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

(ø) The expression representing the loop's terminating condition.

condition - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.IfStatement

(¬ø) The condition controlling execution of the sub-statements.

condition - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.WhileStatement

(¬ø) The expression representing the loop's terminating condition.

Conditional - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents a conditional expression.

Conditional(Expression, Expression, Expression, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Conditional

Full constructor.

CONDITIONAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

confidence - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

The confidence parameter as described above; default SparseConfidenceWeighted.defaultConfidence.

confidence - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted.Parameters

The confidence parameter as described above; default SparseConfidenceWeighted.defaultConfidence.

confidenceInterval(double[], double) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.StudentT

Computes the confidence interval of the specified precision over a set of data points.

conjunction(Feature, Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

Create a feature representing the conjunction of this feature with the given argument feature.

conjunction(Feature, Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Create a feature representing the conjunction of this feature with the given argument feature.

conjunction(Feature, Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealFeature

Create a feature representing the conjunction of this feature with the given argument feature.

CONJUNCTION - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

Conjunction - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents a classifier conjunction.

Conjunction(ClassifierExpression, ClassifierExpression, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Conjunction

Initializing constructor.

CONJUNCTION - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

conjunctiveLabels - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Whether or not this learner's labeler produces conjunctive features.

conjunctiveLabels - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Whether or not this learner's labeler produces conjunctive features.

conjunctiveLabels - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Whether or not this learner's labeler produces conjunctive features.

conjunctiveScores(int[], double[], Iterator) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

This method is a surrogate for SparseMIRA.scores(int[],double[],Collection) when the labeler is known to produce conjunctive features.

conjunctiveScores(int[], double[], Iterator) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

This method is a surrogate for SparseNetworkLearner.scores(int[],double[],Collection) when the labeler is known to produce conjunctive features.

conjunctiveValueOf(int[], double[], Iterator) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

This method is a surrogate for SparseMIRA.valueOf(int[],double[],Collection) when the labeler is known to produce conjunctive features.

conjunctiveValueOf(int[], double[], Iterator) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

This method is a surrogate for SparseNetworkLearner.valueOf(int[],double[],Collection) when the labeler is known to produce conjunctive features.

conjunctiveValueOf(int[], double[], Iterator) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

This method is a surrogate for SupportVectorMachine.valueOf(int[],double[],Collection) when the labeler is known to produce conjunctive features.

conjunctWith(DiscreteFeature, Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

Create a feature representing the conjunction of this feature with the given argument feature.

conjunctWith(DiscreteFeature, Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Create a feature representing the conjunction of this feature with the given argument feature.

conjunctWith(RealFeature, Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Create a feature representing the conjunction of this feature with the given argument feature.

consolidate() - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

After calling this method, the new size and capacity of this vector will be equal to the number of non-null elements; all such elements will be retained in the same relative order.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Constraint

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderBinaryConstraint

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConstant

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityTwoValues

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithValue

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithVariable

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNAryConstraint

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNegation

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalBinaryConstraint

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNAryConstraint

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifiedConstraintInvocation

Replaces all unquantified variables with the unique copy stored as a value of the given map; also instantiates all quantified variables and stores them in the given map.

consolidateVariables(AbstractMap) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Quantifier

Sets the variable map object stored in this object to the given argument; also instantiates all quantified variables and stores them in the map.

CONST - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

constant - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

The constant value.

Constant - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents constant values.

Constant(TokenValue) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Constant

Parser's constructor.

Constant(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Constant

Initializing constructor.

Constant(int, int, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Constant

Full constructor.

ConstantList - Class in edu.illinois.cs.cogcomp.lbjava.IR

Currently, this is just a wrapper class for LinkedList.

ConstantList() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

Default constructor.

ConstantList(Constant) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

Initializing constructor.

ConstantList(String[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

Creates an entire list from an array of values.

ConstantList(ByteString[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

Creates an entire list from an array of values.

ConstantList.ConstantListIterator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Used to iterate though the children of a list of AST nodes.

ConstantListIterator() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList.ConstantListIterator

CONSTRAINT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

Constraint - Class in edu.illinois.cs.cogcomp.lbjava.infer

A constraint is an expression that is either satisified or unsatisfied by its constituent classifier applications.

Constraint() - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.Constraint

constraint - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNegation

The constraint that the negation is applied to.

constraint - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

The constraints which must be satisfied by the inference algorithm.

constraint - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

The constraint that the negation is applied to.

constraint - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifiedConstraintInvocation

The latest result of invoking parameterized.

constraint - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.Quantifier

The constraint being quantified.

constraint - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintStatementExpression

(¬ø) The expression representing the constraint.

constraint - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

(¬ø) The constraint that must be respected during optimization.

constraint - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.NegatedConstraintExpression

(¬ø) The constraint being negated.

constraint - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.QuantifiedConstraintExpression

(¬ø) The quantified constraint.

CONSTRAINT_EQUAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

CONSTRAINT_NOT_EQUAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

ConstraintDeclaration - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents the declaration of a constraint.

ConstraintDeclaration(String, int, int, Name, Argument, Block) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintDeclaration

Full constructor.

ConstraintDeclaration(TokenValue, TokenValue, Argument, Block) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintDeclaration

Parser's constructor.

ConstraintEqualityExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents the atom of the LBJava constraint expression: the (in)equality comparison.

ConstraintEqualityExpression(Operator, Expression, Expression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

Full constructor.

ConstraintExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

Resembling first order logic, a constraint expression consists of equality (or inequality) tests and logical operators and evaluates to a Boolean value.

ConstraintInvocation - Class in edu.illinois.cs.cogcomp.lbjava.IR

A constraint may be invoked from within another constraint using the @ operator.

ConstraintInvocation(int, int, MethodInvocation) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintInvocation

Full constructor.

ConstraintInvocation(TokenValue, MethodInvocation) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintInvocation

Parser's constructor.

constraintsSatisfied(int[]) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Determines whether all constraints are satisfied by the given solution.

ConstraintStatementExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class is simply a wrapper for a ConstraintExpression so that it can be used in an ExpressionStatement.

ConstraintStatementExpression(ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintStatementExpression

Full constructor.

ConstraintType - Class in edu.illinois.cs.cogcomp.lbjava.IR

A constraint's type is defined by what it takes as input.

ConstraintType(Type) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintType

Initializing constructor.

containingPackage - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

The name of the package containing this classifier.

containingPackage - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

The Java package containing the classifier that produced this feature.

contains(FirstOrderConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNAryConstraint

Determines whether the given constraint is a term of this constraint.

contains(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Determines whether the given constraint is a term of this constraint.

contains(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNAryConstraint

Determines whether the given constraint is a term of this constraint.

contains(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Returns true if the given feature is already in the lexicon (whether it's past the Lexicon.pruneCutoff or not) and false otherwise.

containsAll(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Determines whether this conjunction contains all of the terms that the given conjunction contains.

containsAll(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Determines whether this disjunction contains all of the terms that the given disjunction contains.

containsKey(ClassifierName) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Determines whether the specified name has been used as a key in this table or any of its parents.

containsKey(Name) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Determines whether the specified name has been used as a key in this table or any of its parents.

containsKey(String) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Determines whether the specified name has been used as a key in this table or any of its parents.

containsQuantifiedVariable() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

Determines if there are any quantified variables in this expression.

containsQuantifiedVariable() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintExpression

Determines if there are any quantified variables in this expression.

containsQuantifiedVariable() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintInvocation

Determines if there are any quantified variables in this expression.

containsQuantifiedVariable() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintStatementExpression

Determines if there are any quantified variables in this expression.

containsQuantifiedVariable() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Expression

Determines if there are any quantified variables in this expression.

containsQuantifiedVariable() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList

Determines if there are any quantified variables in this expression.

containsQuantifiedVariable() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Determines if there are any quantified variables in this expression.

containsQuantifiedVariable() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Name

Determines if there are any quantified variables in this expression.

containsQuantifiedVariable(boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Name

Determines if there are any quantified variables in this expression.

containsTypeSpecificNormalizer() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Returns true iff at least one of the normalizer declarations is specific to a given type.

context - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ArgumentReplacer

The settings of non-quantification variables in context at the equality in question.

contFract(double, double, double) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.StudentT

Incomplete fraction summation used in the method StudentT.regularisedBetaFunction(double,double,double).

CONTINUE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

ContinueStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a continue statement.

ContinueStatement(String, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ContinueStatement

Full constructor.

convertRange() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Converts this parameter set's ParameterSet.start, ParameterSet.end, and ParameterSet.increment expressions (which must represent Constants of a PrimitiveType other than boolean) into an explicit list of values.

correctExample() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Increments the SparseAveragedPerceptron.AveragedWeightVector.examples variable.

correctHistogram - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

The histogram of correct predictions.

count - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Remembers how many instances of this class have been instantiated.

Count() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Count

Sets the count to 0.

count - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Count

The accumulated value.

countFeatures(Lexicon.CountPolicy) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Establishes a new feature counting policy for this learner's lexicon.

countFeatures(Lexicon.CountPolicy) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Call this method to initialize the lexicon to count feature occurrences on each call to lookup(feature, true) (counting still won't happen on a call to lookup(feature, false)).

counts - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

The counts in the vector indexed by their Lexicon key.

createPrediction(int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

If it hasn't been created already, this method will create the prediction feature in Learner.predictions associated with the label feature at the given index of Learner.labelLexicon.

createPrediction(Lexicon, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

If it hasn't been created already, this method will create the prediction feature in Learner.predictions associated with the label feature at the given index of lex .

createVariable(String) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Creates a new Boolean variable to represent the value of a subexpression of some constraint.

crossValidation(int[], int, FoldParser.SplitPolicy, double, TestingMetric, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Performs cross validation, computing a confidence interval on the performance of the learner after each of the specified rounds of training.

crossValidationTesting(FoldParser, TestingMetric, boolean, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Tests the learner as a subroutine inside cross validation.

cutLast() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Name

Returns a new Name object that is the same as this Name object, except the last identifier has been removed.

CVAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

CVAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Value of the type variable.

cvalClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Counts the number of cval clauses for error detection.

D

data - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SynchronizedStatement

(¬ø) The expression representing the data to be protected.

Declaration - Class in edu.illinois.cs.cogcomp.lbjava.IR

Abstract representation of declarations such as import and package.

Declaration(Name, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Declaration

Initializing constructor.

Declaration(String, Name, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Declaration

Full constructor.

DeclarationList - Class in edu.illinois.cs.cogcomp.lbjava.IR

Currently, this is just a wrapper class for LinkedList.

DeclarationList() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.DeclarationList

Default constructor.

DeclarationList(Declaration) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.DeclarationList

Initializing constructor.

DeclarationList.DeclarationListIterator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Used to iterate though the children of a list of AST nodes.

DeclarationListIterator() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.DeclarationList.DeclarationListIterator

DeclarationNames - Class in edu.illinois.cs.cogcomp.lbjava

DeclarationNames(AST) - Constructor for class edu.illinois.cs.cogcomp.lbjava.DeclarationNames

Instantiates a pass that runs on an entire AST.

declarations - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.AST

(¬ø) The list of classifier, constraint, and inference declarations representing the LBJava program.

decrementParentCounts(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

The parent of feature f is being removed, so we decrement f's parent counts and remove it if it's ready.

DEFAULT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

defaultAlpha - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

If no alpha clause appears during cross validation, this constant is used.

defaultAttributeString - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Default for the WekaWrapper.attributeString field.

defaultBaseClassifier - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Default for the WekaWrapper.baseClassifier field.

defaultBaseLearner - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Default for MuxLearner.baseLearner.

defaultBaseLTU - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Default for SparseNetworkLearner.baseLTU.

defaultBeta - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Default value for BinaryMIRA.beta.

defaultBias - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Default for SupportVectorMachine.bias.

defaultC - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Default for SupportVectorMachine.C.

defaultCapacity - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

The initial capacity for SparseWeightVector.weights if not specified otherwise.

defaultCapacity - Static variable in class edu.illinois.cs.cogcomp.lbjava.util.FVector

The default capacity of a vector upon first construction.

defaultConfidence - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Default value for SparseConfidenceWeighted.confidence.

defaultDefaultPrediction - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Default for MuxLearner.defaultPrediction.

defaultDiscreteLearner - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

If no learning algorithm is specified to learn a discrete classifier, this learner is used.

defaultEncoding - Static variable in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

The default character encoding for instances of this class.

defaultEpsilon - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Default for SupportVectorMachine.epsilon.

defaultFeature - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

A feature whose value is MuxLearner.defaultPrediction.

defaultFiles(CodeGenerator) - Method in class edu.illinois.cs.cogcomp.lbjava.Clean

Adds the default files (*.java and *.class) to the remove list.

defaultInferenceConstructor - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

If no inference algorithm is specified, this algorithm is used.

defaultInitialBias - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

Default value for BiasedWeightVector.initialBias.

defaultInitialVariance - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Default value for SparseConfidenceWeighted.initialVariance.

defaultInitialWeight - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Default for LinearThresholdUnit.initialWeight.

defaultInitialWeight - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Default for LinearThresholdUnit.initialWeight.

defaultLearningRate - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

defaultLearningRate - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Default value for LinearThresholdUnit.learningRate.

defaultLearningRate - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Default value for LinearThresholdUnit.learningRate.

defaultLearningRate - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Default for LinearThresholdUnit.learningRate.

defaultLearningRate - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Default value for StochasticGradientDescent.learningRate.

defaultLossFunction - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

defaultPrediction - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

This string is returned during testing when the multiplexed Learner doesn't exist; default MuxLearner.defaultDefaultPrediction.

defaultPrediction - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner.Parameters

This string is returned during testing when the multiplexed Learner doesn't exist; default MuxLearner.defaultDefaultPrediction.

defaultPreExtract - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

If no preExtract clause appears in the sources, this constant is used.

defaultRealLearner - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

If no learning algorithm is specified to learn a real classifier, this learner is used.

defaultRounds - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Default for AdaBoost.rounds.

defaultSmoothing - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

The default conditional feature probability is e^{defaultSmoothing} .

defaultSolverType - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Default for SupportVectorMachine.solverType.

defaultStddev - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

Default value for RandomWeightVector.stddev.

defaultThickness - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Default for LinearThresholdUnit.positiveThickness.

defaultThreshold - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Default for LinearThresholdUnit.threshold.

defaultThreshold - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Default for LinearThresholdUnit.threshold.

defaultWeakLearner - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Default for AdaBoost.weakLearner.

defaultWeight - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

When a feature appears in an example but not in this vector, it is assumed to have this weight.

defaultWeightVector - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Default for LinearThresholdUnit.weightVector.

defaultWeightVector - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Default for LinearThresholdUnit.weightVector.

defaultWeightVector - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Default for StochasticGradientDescent.weightVector.

demandLexicon() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Forces this learner to read in its lexicon representation, but only if the lexicon currently available in this object is empty and the learner has been scheduled to read its lexicon on demand with Learner.readLexiconOnDemand(URL).

demote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Scales the feature vector produced by the extractor by the learning rate and subtracts it from the weight vector.

demote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

If the LinearThresholdUnit is mistake driven, this method should be overridden and used to update the internal representation when a mistake is made on a negative example.

demote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Scales the feature vector produced by the extractor by the learning rate and subtracts it from the weight vector.

demote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Scales the feature vector produced by the extractor by the learning rate and subtracts it from the weight vector.

demote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

This method does nothing.

demote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Scales the feature vector produced by the extractor by the learning rate and subtracts it from the weight vector.

demote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Demotion is simply w_i *= betax_i.

dependorGraph - Static variable in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

The keys of this map are the names of CodeGenerators; the values are HashSets of names of other locally defined CodeGenerators that depend on the CodeGenerator named by the associated key.

depth() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

The depth of a feature is one more than the maximum depth of any of its children, or 0 if it has no children.

depth() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

The depth of a feature is one more than the maximum depth of any of its children, or 0 if it has no children.

depth() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

The depth of a feature is one more than the maximum depth of any of its children, or 0 if it has no children.

depth() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

The depth of a feature is one more than the maximum depth of any of its children, or 0 if it has no children.

depth() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

The depth of a feature is one more than the maximum depth of any of its children, or 0 if it has no children.

dimensions - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayCreationExpression

The total number of dimensions, including those for which no size is given.

dimensions - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Name

The number of matched brackets appearing after a single identifier; supports variable declarations.

discardPrunedFeatures() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Permanently discards any features that have been pruned via Lexicon.prune(Lexicon.PruningPolicy) as well as all feature counts.

disclaimer - Static variable in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

The commented message appearing at the top of all generated files.

DISCRETE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

DISCRETE - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Value of the type variable.

DISCRETE_ARRAY - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Value of the type variable.

DISCRETE_GENERATOR - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Value of the type variable.

DiscreteArrayFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A discrete array feature keeps track of its index in the classifier's returned array as well as the total number of features in that array.

DiscreteArrayFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

For internal use only.

DiscreteArrayFeature(String, String, ByteString, ByteString, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Sets the identifier, value, array index, and size of the containing array.

DiscreteArrayFeature(String, String, ByteString, ByteString, short, short, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Sets all member variables.

DiscreteArrayStringFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A discrete array feature keeps track of its index in the classifier's returned array as well as the total number of features in that array.

DiscreteArrayStringFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

For internal use only.

DiscreteArrayStringFeature(String, String, String, String, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Sets the identifier, value, array index, and size of the containing array.

DiscreteArrayStringFeature(String, String, String, String, short, short, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Sets all member variables.

DiscreteConjunctiveFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

Represents the conjunction of two discrete features.

DiscreteConjunctiveFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

For internal use only.

DiscreteConjunctiveFeature(String, String, DiscreteFeature, DiscreteFeature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Creates a new conjunctive feature.

DiscreteConjunctiveFeature(String, String, DiscreteFeature, DiscreteFeature, short, short) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Creates a new conjunctive feature.

DiscreteConjunctiveFeature(Classifier, DiscreteFeature, DiscreteFeature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Creates a new conjunctive feature taking the package and name of the given classifier.

DiscreteFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A discrete feature takes on one value from a set of discontinuous values.

DiscretePrimitiveFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A primitive discrete feature is a discrete feature with a string value.

DiscretePrimitiveFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

For internal use only.

DiscretePrimitiveFeature(String, String, ByteString, ByteString) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Sets both the identifier and the value.

DiscretePrimitiveFeature(String, String, ByteString, ByteString, short, short) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Sets the identifier, value, value index, and total allowable values.

DiscretePrimitiveStringFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

This feature is functionally equivalent to DiscretePrimitiveFeature, however its DiscretePrimitiveStringFeature.value is stored as a String instead of a ByteString.

DiscretePrimitiveStringFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

For internal use only.

DiscretePrimitiveStringFeature(String, String, String, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Sets both the identifier and the value.

DiscretePrimitiveStringFeature(String, String, String, String, short, short) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Sets the identifier, value, value index, and total allowable values.

DiscreteReferrer - Class in edu.illinois.cs.cogcomp.lbjava.classify

A referring discrete feature is one that has its own identifier, but whose value comes from a separate feature that it refers to.

DiscreteReferrer() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

For internal use only.

DiscreteReferrer(Classifier, DiscreteFeature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Sets both the identifier and the referent.

DiscreteReferrer(Classifier, DiscreteFeature, String[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Sets both the identifier and the referent.

DiscreteReferrer(String, String, DiscreteFeature, short, short) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Constructs a new referring feature.

DiscreteReferringFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A referring discrete feature is one that has its own identifier, but whose value comes from a separate feature that it refers to.

DiscreteReferringFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

For internal use only.

DiscreteReferringFeature(Classifier, ByteString, DiscreteFeature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Sets both the identifier and the referent.

DiscreteReferringFeature(Classifier, ByteString, DiscreteFeature, String[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Sets both the identifier and the referent.

DiscreteReferringFeature(String, String, ByteString, DiscreteFeature, short, short) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Constructs a new referring feature.

DiscreteReferringStringFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A referring discrete feature is one that has its own identifier, but whose value comes from a separate feature that it refers to.

DiscreteReferringStringFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

For internal use only.

DiscreteReferringStringFeature(Classifier, String, DiscreteFeature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Sets both the identifier and the referent.

DiscreteReferringStringFeature(Classifier, String, DiscreteFeature, String[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Sets both the identifier and the referent.

DiscreteReferringStringFeature(String, String, String, DiscreteFeature, short, short) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Constructs a new referring feature.

discreteValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Returns the value of the discrete feature that would be returned by this classifier.

discreteValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.MultiValueComparer

Returns the value of the discrete feature that would be returned by this classifier.

discreteValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ValueComparer

Returns the value of the discrete feature that would be returned by this classifier.

discreteValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

This method uses the trained parameters to make a binary decision about an example object.

discreteValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the value of the discrete prediction that this learner would make, given an example.

discreteValue(FeatureVector) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the value of the discrete prediction that this learner would make, given a feature vector.

discreteValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the value of the discrete feature that would be returned by this classifier.

discreteValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

The default evaluation method simply computes the score for the example and returns a DiscretePrimitiveStringFeature set to either the second value from the label classifier's array of allowable values if the score is greater than or equal to LinearThresholdUnit.threshold or the first otherwise.

discreteValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Returns the value of the discrete feature that would be returned by this classifier.

discreteValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Prediction value counts and feature counts given a particular prediction value are used to select the most likely prediction value.

discreteValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

This implementation uses a winner-take-all comparison of the individual weight vectors' dot products.

discreteValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

This implementation uses a winner-take-all comparison of the outputs from the individual linear threshold units' score methods.

discreteValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

The evaluate method returns the class label which yields the highest score for this example.

discreteValueArray(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Returns the values of the discrete array of features that would be returned by this classifier.

discreteValueArray() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns all the values of the features in this vector (not labels) arranged in a String array.

DISJUNCTION - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

displayLL - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Controls if liblinear-related messages are output

displayLL - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine.Parameters

Determines if liblinear-related output should be displayed; default false

distribute(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Distributes the given disjunction over this conjunction.

distribute(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Distributes the given conjunction over this disjunction.

DIVEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

DIVIDE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

DIVIDE - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

DIVIDE_ASSIGN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

DNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Produces a new, logically simplified version of this constraint in disjunctive normal form (DNF).

DNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Produces a new, logically simplified version of this constraint in disjunctive normal form (DNF).

DNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Produces a new, logically simplified version of this constraint in disjunctive normal form (DNF).

DNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Produces a new, logically simplified version of this constraint in disjunctive normal form (DNF).

DNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Produces a new, logically simplified version of this constraint in disjunctive normal form (DNF).

DNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Produces a new, logically simplified version of this constraint in disjunctive normal form (DNF).

DNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Produces a new, logically simplified version of this constraint in disjunctive normal form (DNF).

DNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Produces a new, logically simplified version of this constraint in disjunctive normal form (DNF).

DNF() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Produces a new, logically simplified version of this constraint in disjunctive normal form (DNF).

DO - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

do_action(int, lr_parser, Stack, int) - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Invoke a user supplied parse action.

doneLearning() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Performs learning on the examples stored in AdaBoost.allExamples, if they exist; otherwise do nothing.

doneLearning() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Overridden by subclasses to perform any required post-processing computations after all training examples have been observed through Learner.learn(Object) and Learner.learn(Object[]).

doneLearning() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Simply calls doneLearning() on every LTU in the network.

doneLearning() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

This method converts the arrays of examples stored in this class into input for the liblinear training method.

doneLearning() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Indicates that the classifier is finished learning.

doneWithRound(int) - Method in interface edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer.DoneWithRound

The hook into BatchTrainer.train(int) as described above.

doneWithRound() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Called after each round of training.

doneWithRound() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Simply calls Learner.doneWithRound() on every LTU in the network.

DoStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a while loop.

DoStatement(Statement, Expression, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.DoStatement

Full constructor.

dot(int[], double[], int[], double[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Computes the dot product of the 2 argument vectors.

dot(FeatureVector) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Take the dot product of two feature vectors.

DOT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

DOT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

dot(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedRandomWeightVector

Takes the dot product of this BiasedRandomWeightVector with the argument vector, using the specified default weight when one is not yet present in this vector.

dot(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

Takes the dot product of this BiasedWeightVector with the argument vector, using the specified default weight when one is not yet present in this vector.

dot(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Takes the dot product of this vector with the given vector, using the hard coded smoothing weight.

dot(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Takes the dot product of this vector with the given vector, using the specified default weight when encountering a feature that is not yet present in this vector.

dot(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Takes the dot product of this AveragedWeightVector with the argument vector, using the hard coded default weight.

dot(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Takes the dot product of this AveragedWeightVector with the argument vector, using the specified default weight when one is not yet present in this vector.

dot(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Takes the dot product of this SparseWeightVector with the argument vector, using the hard coded default weight.

dot(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Takes the dot product of this SparseWeightVector with the argument vector, using the specified default weight when one is not yet present in this vector.

DOTDOT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

DOUBLE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

DOUBLE - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Value of the type variable.

DOUBLE_IMPLICATION - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

DOUBLEIMPLICATION - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

E

edu.illinois.cs.cogcomp.lbjava - package edu.illinois.cs.cogcomp.lbjava

edu.illinois.cs.cogcomp.lbjava.classify - package edu.illinois.cs.cogcomp.lbjava.classify

edu.illinois.cs.cogcomp.lbjava.frontend - package edu.illinois.cs.cogcomp.lbjava.frontend

edu.illinois.cs.cogcomp.lbjava.infer - package edu.illinois.cs.cogcomp.lbjava.infer

edu.illinois.cs.cogcomp.lbjava.io - package edu.illinois.cs.cogcomp.lbjava.io

edu.illinois.cs.cogcomp.lbjava.IR - package edu.illinois.cs.cogcomp.lbjava.IR

edu.illinois.cs.cogcomp.lbjava.learn - package edu.illinois.cs.cogcomp.lbjava.learn

edu.illinois.cs.cogcomp.lbjava.parse - package edu.illinois.cs.cogcomp.lbjava.parse

edu.illinois.cs.cogcomp.lbjava.util - package edu.illinois.cs.cogcomp.lbjava.util

elementType - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayCreationExpression

(¬ø) The most basic type of elements in the array (i.e., it will not be an ArrayType).

ELSE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

elseClause - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Conditional

(¬ø) The expression to evaluate if the condition evaluates to false.

elseClause - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.IfStatement

(ø) The statement to execute if the condition is false, if any.

emptyClone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedRandomWeightVector

Returns a new, empty weight vector with the same parameter settings as this one.

emptyClone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

Returns a new, empty weight vector with the same parameter settings as this one.

emptyClone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns a new, emtpy learner into which all of the parameters that control the behavior of the algorithm have been copied.

emptyClone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Returns a new, empty weight vector with the same parameter settings as this one.

emptyClone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

Returns a new, empty weight vector with the same parameter settings as this one.

emptyClone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Returns a new, empty weight vector with the same parameter settings as this one.

emptyClone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Returns a new, empty weight vector with the same parameter settings as this one.

EmptyStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

No statement here.

EmptyStatement(int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.EmptyStatement

Full constructor.

emptyString - Static variable in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

A byte string representing "".

enclosingQuantificationSettings - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.Quantifier

A list of the objects stored in the quantification variables of enclosing quantifiers.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

encode(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Returns a feature object in which any strings that are being used to represent an identifier or value have been encoded in byte strings.

ENCODING - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

ENCODING - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Value of the type variable

encoding - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

The encoding used by this learner's feature lexicon.

encoding - Variable in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

The encoding method used by this instance.

encodingClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Counts the number of encoding clauses for error detection.

END - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

end - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

The end value for the range.

end - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedChild

The offset into the raw data input file at which this child ends.

EOF - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

EOF_sym() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

EOF Symbol index.

epsilon - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

The tolerance of termination criterion; default SupportVectorMachine.defaultEpsilon.

epsilon - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine.Parameters

The tolerance of termination criterion; default SupportVectorMachine.defaultEpsilon.

EQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

EQEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

EQUAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

equality - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEquality

true if equality, false if inequality.

EQUALITY - Static variable in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Represents the constraint type "equality".

EqualityArgumentReplacer - Class in edu.illinois.cs.cogcomp.lbjava.infer

Anonymous inner classes extending this class are instantiated by the code generated by the LBJava compiler when creating FirstOrderConstraint representations.

EqualityArgumentReplacer(Object[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.EqualityArgumentReplacer

Initializing constructor.

EqualityArgumentReplacer(Object[], boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.EqualityArgumentReplacer

Use this constructor to indicate which of the two arguments of the equality is in fact not quantified.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Two DiscreteArrayFeatures are equivalent when their containing packages, identifiers, indices, and values are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Two DiscreteArrayStringFeatures are equivalent when their containing packages, identifiers, indices, and values are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Two conjunctions are equivalent when their arguments are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Two DiscretePrimitive(String)Features are equivalent when their containing packages, identifiers, and values are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Two DiscretePrimitiveStringFeatures are equivalent when their containing packages, identifiers, and values are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Two DiscreteReferringFeatures are equivalent when their containing packages, identifiers, and referent features are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Two DiscreteReferringStringFeatures are equivalent when their containing packages, identifiers, and referent features are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Two Features are equal when their packages and generating classifiers are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Two FeatureVectors are equivalent if they contain the same features and labels, as defined by Feature equivalence.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Two RealArrayFeatures are equivalent when their containing packages, identifiers, indices, and values are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Two RealArrayStringFeatures are equivalent when their containing packages, identifiers, indices, and values are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Two conjunctions are equivalent when their arguments are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Two RealPrimitiveFeatures are equivalent when their containing packages and identifiers are equivalent and their values are equal.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Two RealPrimitiveStringFeatures are equivalent when their containing packages and identifiers are equivalent and their values are equal.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Two RealReferringFeatures are equivalent when their containing packages, identifiers, and referent features are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Two RealReferringStringFeatures are equivalent when their containing packages, identifiers, and referent features are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.AtLeastQuantifier

Two AtLeastQuantifiers are equivalent when their children are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.AtMostQuantifier

Two AtMostQuantifiers are equivalent when their children are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ExistentialQuantifier

Two ExistentialQuantifiers are equivalent when their children are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConjunction

Two FirstOrderConjunctions are equivalent when they are topologically equivalent, respecting the associativity and commutivity of disjunction.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConstant

Two FirstOrderConstants are equivalent when their constants are equal.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDisjunction

Two FirstOrderDisjunctions are equivalent when they are topologically equivalent, respecting the associativity and commutivity of disjunction.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDoubleImplication

Two FirstOrderDoubleImplications are equivalent when they are topologically equivalent, respecting the commutativity of double implication.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityTwoValues

Two FirstOrderEqualityTwoValuess are equivalent when their children are equivalent in either order.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithValue

Two FirstOrderEqualityWithValues are equivalent when their children are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithVariable

Two FirstOrderEqualityWithVariables are equivalent when their children are equivalent in either order.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderImplication

Two FirstOrderImplications are equivalent when they are topologically equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNegation

Two FirstOrderNegations are equivalent when their constraints are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderVariable

Two FirstOrderVariables are equivalent when their classifiers are equivalent and they store the same example object.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Two Inference objects are equal when they have the same run-time type and store the same head object.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Two PropositionalAtLeasts are equivalent when they are topologically equivalent; this implementation currently does not respect the associativity and commutativity of at-least.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Two PropositionalConjunctions are equivalent when they are topologically equivalent, respecting the associativity and commutivity of conjunction.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Two PropositionalConstants are equivalent when their constants are equal.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Two PropositionalDisjunctions are equivalent when they are topologically equivalent, respecting the associativity and commutivity of disjunction.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Two PropositionalDoubleImplications are equivalent when they are topologically equivalent, respecting the commutativity of double implication.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Two PropositionalImplications are equivalent when they are topologically equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Two PropositionalNegations are equivalent when their constraints are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Two PropositionalVariables are equivalent when the string representations of their classifiers are equivalent, they store the same example object, and their values are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifiedConstraintInvocation

Two QuantifiedConstraintInvocations are equivalent when their children are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Quantifier

Two Quantifiers are equivalent when their children are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.UniversalQuantifier

Two UniversalQuantifiers are equivalent when their children are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Argument

Two Arguments are equivalent when their names and types are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayCreationExpression

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayInitializer

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayType

Two ArrayTypes are equivalent if their child types are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AssertStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Assignment

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryExpression

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Block

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BreakStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CastExpression

Determines if this object is equivalent to another object.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchClause

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierCastExpression

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierName

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Determines whether the argument is equal to this object.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

Two ClassifierTypes are equivalent when their input types match.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CodedClassifier

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CompositeGenerator

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conditional

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conjunction

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Constant

Two constants are equal when their noQuotes() methods return the same thing.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

Two ConstantLists are equal when they contain the same elements in the same order as evaluated by the Constant.equals(Object) method.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintType

Two ConstraintTypes are equivalent when their input types match.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ContinueStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.EmptyStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.FieldAccess

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.IfStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.IncrementExpression

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceInvocation

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

Two InferenceTypes are equivalent when their head types match.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InstanceCreationExpression

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InstanceofExpression

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LabeledStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List

Determines whether this list is equivalent to another object.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Name

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NormalizerType

Any two NormalizerTypes are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Two parameter sets are equivalent when their constituent expressions are the same.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Two PrimitiveTypes are equivalent when their type member variables are the same.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReferenceType

Two ReferenceTypes are equivalent when their associated Java class es, as computed by typeClass() are equivalent.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReturnStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SubscriptVariable

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroup

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabel

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SynchronizedStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ThrowStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.TryStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.UnaryExpression

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.WhileStatement

Distinguishes this ASTNode from other objects according to its contents recursively.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Returns whether the given Lexicon object is equal to this one.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Two byte strings are equivalent if they encode the same string.

equals(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Two FVectors are considered equal if they contain equivalent elements and have the same size.

error - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

error_sym() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

error Symbol index.

escapeFilePath(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.FileUtils

Escapes the forward slash in Windows.

EVALUATE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.AtLeastQuantifier

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.AtMostQuantifier

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Constraint

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ExistentialQuantifier

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConjunction

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConstant

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDisjunction

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDoubleImplication

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityTwoValues

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithValue

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithVariable

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderImplication

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNegation

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Determines whether the constraint is satisfied.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifiedConstraintInvocation

If this method is called without first calling setQuantificationVariables(Vector), false will be returned.

evaluate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.UniversalQuantifier

Determines whether the constraint is satisfied.

evaluate(int[]) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

This method evaluates the objective function on a potential (not necessarily feasible) solution.

EVALUATE - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Value of the type variable.

evaluateClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Counts the number of evaluate clauses for error detection.

evaluation - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) Tells this learning classifier how to produce a prediction during evaluation; argument to evaluate.

example - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

The classifier is applied to this example object.

exampleData - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

A single array from which all examples can be parsed.

exampleFileName - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

The name of the file to parse.

exampleIndex - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Keeps track of the index of the next example to be returned.

examples - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

The number of examples extracted during pre-extraction.

examples - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Counts the total number of training examples this vector has seen.

examples - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayParser

An array of examples, returned one at a time by the parser.

examples - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

The total number of examples coming from FoldParser.parser.

exampleToString(Object) - Static method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Produces a string representation of an example object.

exception - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ThrowStatement

(¬ø) The expression representing the exception to throw.

executeReadyThreads(String) - Method in class edu.illinois.cs.cogcomp.lbjava.Train

This method updates the Train.learnerDependencies graph by removing the specified name from every dependencies list, and then starts every thread that has no more dependencies.

exFilePath - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

The file into which training examples are extracted.

ExistentialQuantifier - Class in edu.illinois.cs.cogcomp.lbjava.infer

An existential quantifier states that the constraint must hold for at least one object from the collection.

ExistentialQuantifier(String, Collection, FirstOrderConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ExistentialQuantifier

Initializing constructor.

ExistentialQuantifier(String, Collection, FirstOrderConstraint, QuantifierArgumentReplacer) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ExistentialQuantifier

This constructor specifies a variable setter for when this quantifier is itself quantified.

ExistentialQuantifierExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

An existential quantifier has the form: exists argument in (expression) constraint-expression where expression must evaluate to a Collection, and the existential quantifier expression is sastisfied iff constraint-expression is satisfied for any setting of argument taken from the Collection.

ExistentialQuantifierExpression(int, int, Argument, Expression, ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ExistentialQuantifierExpression

Full constructor.

ExistentialQuantifierExpression(TokenValue, Argument, Expression, ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ExistentialQuantifierExpression

Parser's constructor.

EXISTS - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

existsInClasspath(Class, String) - Static method in class edu.illinois.cs.cogcomp.lbjava.io.IOUtilities

expandFor(int, Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Makes sure the capacity and size of the vector can accomodate the given index.

expression - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.CastExpression

(¬ø) The expression whose value should be casted.

expression - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

(¬ø) The expression representing the classifier.

expression - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierCastExpression

(¬ø) The expression being casted.

Expression - Class in edu.illinois.cs.cogcomp.lbjava.IR

Abstract expression class.

expression - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionStatement

(¬ø) The expression being used as a statement.

expression - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ReturnStatement

(¬ø) The expression representing the value to return.

expression - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchStatement

(¬ø) The expression determining which statements to execute.

ExpressionList - Class in edu.illinois.cs.cogcomp.lbjava.IR

Currently, this is just a wrapper class for LinkedList.

ExpressionList() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList

Default constructor.

ExpressionList(Expression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList

Initializing constructor.

ExpressionList(Expression, ExpressionList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList

Initializing constructor.

ExpressionList.ExpressionListIterator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Used to iterate though the children of a list of AST nodes.

ExpressionListIterator() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList.ExpressionListIterator

ExpressionStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

An expression statement is a statement composed only of a single expression, as opposed to a statement involving control flow.

ExpressionStatement(StatementExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionStatement

Initializing constructor.

EXTENDS - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

extractor - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(¬ø) The classifier that does feature extraction for this classifier; argument to using.

extractor - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Stores the classifiers used to produce features.

F

factor() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Factoring a conjunction is the opposite of distributing a disjunction over a conjunction.

factor() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Factoring a disjunction is the opposite of distributing a conjunction over a disjunction.

factorial(double) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.StudentT

factorial of n.

False - Static variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

false

fatalError - Static variable in class edu.illinois.cs.cogcomp.lbjava.Pass

This flag gets set if an error occurs that should cause the LBJava compiler to stop executing after this pass finishes.

Feature - Class in edu.illinois.cs.cogcomp.lbjava.classify

Objects of this class represent the value of a Classifier's decision.

Feature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.Feature

For internal use only.

Feature(String, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Initializing constructor.

featureCounts - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Counts the number of occurrences of each feature.

featureEncoding - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) The encoding that the generated classifier will use when storing string data in features.

features - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Stores non-label features.

featuresSize() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns the size of just the FeatureVector.features list.

featuresStatus - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

The revision status of the LCE's features node.

featureValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Returns the classification of the given example object as a single feature instead of a FeatureVector.

featureValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.MultiValueComparer

Returns the classification of the given example object as a single feature instead of a FeatureVector.

featureValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ValueComparer

Returns the classification of the given example object as a single feature instead of a FeatureVector.

featureValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ParameterizedConstraint

Returns the classification of the given example object as a single feature instead of a FeatureVector.

featureValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Returns the classification of the given example as a single feature instead of a FeatureVector.

featureValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Returns the classification of the given example as a single feature instead of a FeatureVector.

featureValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the classification of the given example object as a single feature instead of a FeatureVector.

featureValue(FeatureVector) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the classification of the given feature vector as a single feature instead of a FeatureVector.

featureValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the classification of the given example as a single feature instead of a FeatureVector.

featureValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Returns the classification of the given example as a single feature instead of a FeatureVector.

featureValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Returns the classification of the given example as a single feature instead of a FeatureVector.

featureValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Returns the classification of the given example as a single feature instead of a FeatureVector.

featureValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Returns the classification of the given example as a single feature instead of a FeatureVector.

featureValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Returns the classification of the given example as a single feature instead of a FeatureVector.

featureValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Returns the classification of the given example as a single feature instead of a FeatureVector.

featureValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Returns the classification of the given example as a single feature instead of a FeatureVector.

FeatureVector - Class in edu.illinois.cs.cogcomp.lbjava.classify

Objects of this class are returned by classifiers that have been applied to an object.

FeatureVector() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Simply instantiates the member variables.

FeatureVector(Feature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Creates the vector and adds the given feature to it.

FeatureVector(Feature[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Creates the vector and adds the given features to it.

FeatureVector(Object[], Lexicon, Lexicon) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Instantiates a feature vector from example arrays and lexicons.

FeatureVectorReturner - Class in edu.illinois.cs.cogcomp.lbjava.classify

This classifier expects FeatureVectors as input, and it simply returns them as output.

FeatureVectorReturner() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVectorReturner

Default constructor.

FieldAccess - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents a field access.

FieldAccess(Expression, TokenValue) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.FieldAccess

Parser's constructor.

FieldAccess(Expression, String, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.FieldAccess

Full constructor.

fieldIsTraining - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

BatchTrainer.learner's isTraining field.

filename - Variable in class edu.illinois.cs.cogcomp.lbjava.frontend.TokenValue

The name of the source file.

fileName - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.LineByLine

The name of the file to parse.

fileNames - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

A list of names of files generated by the compiler, created as they are generated.

FileUtils - Class in edu.illinois.cs.cogcomp.lbjava.util

Utility methods for handling file paths.

FileUtils() - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.FileUtils

fillInSizes() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

This method sets the BatchTrainer.examples and BatchTrainer.lexiconSize variables by querying BatchTrainer.parser and BatchTrainer.learner respectively.

fillLearnerDependorsDAG() - Method in class edu.illinois.cs.cogcomp.lbjava.Train

This method initializes the Train.learnerDependencies graph such that the entry for each learner contains the names of all learners that depend on it, except that cycles are broken by preferring that learners appearing earlier in the source get trained first.

filter(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Convenient for determining if the next example should be returned or not.

FINAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

FINALLY - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

finallyBlock - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.TryStatement

(ø) The block of the "finally" clause, if any.

findFile(String, String, String) - Static method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Given the name of a class, which may or may not be fully qualified, this method returns the absolute path to the file with the same name and the given extension.

first - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Whether or not the algorithm will halt upon finding its first feasible solution.

first - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Log

This normalizer runs before applying the log function.

firstFeature() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns the first feature in FeatureVector.features.

firstLabel() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns the first feature in FeatureVector.labels.

FirstOrderBinaryConstraint - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents a first order constraint involving a binary operator.

FirstOrderBinaryConstraint(FirstOrderConstraint, FirstOrderConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderBinaryConstraint

Initializing constructor.

FirstOrderConjunction - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents the conjunction of first order constraints.

FirstOrderConjunction(FirstOrderConstraint, FirstOrderConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConjunction

If either of the arguments is itself a FirstOrderConjunction, its contents are flattened into this FirstOrderConjunction.

FirstOrderConstant - Class in edu.illinois.cs.cogcomp.lbjava.infer

A first order constant is either true or false.

FirstOrderConstant(boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConstant

Initializing constructor.

FirstOrderConstraint - Class in edu.illinois.cs.cogcomp.lbjava.infer

All classes for representing first order constraints are derived from this base class.

FirstOrderConstraint() - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConstraint

FirstOrderDisjunction - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents the disjunction of first order constraints.

FirstOrderDisjunction(FirstOrderConstraint, FirstOrderConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDisjunction

If either of the arguments is itself a FirstOrderDisjunction, its contents are flattened into this FirstOrderDisjunction.

FirstOrderDoubleImplication - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents a double implication between two first order constraints.

FirstOrderDoubleImplication(FirstOrderConstraint, FirstOrderConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDoubleImplication

Initializing constructor.

FirstOrderEquality - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents either an equality or an inequality between two values, a classifier application and a value, or two classifier applications.

FirstOrderEquality(boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEquality

Initializing constructor.

FirstOrderEquality(boolean, EqualityArgumentReplacer) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEquality

This constructor specifies a variable setter for when this equality is quantified.

FirstOrderEqualityTwoValues - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents the comparison of two String values.

FirstOrderEqualityTwoValues(boolean, String, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityTwoValues

Initializing constructor.

FirstOrderEqualityTwoValues(boolean, String, String, EqualityArgumentReplacer) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityTwoValues

This constructor specifies a variable setter for when this equality is quantified.

FirstOrderEqualityWithValue - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents the comparison of a classifier application with a value.

FirstOrderEqualityWithValue(boolean, FirstOrderVariable, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithValue

Initializing constructor.

FirstOrderEqualityWithValue(boolean, FirstOrderVariable, String, EqualityArgumentReplacer) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithValue

This constructor specifies a variable setter for when this equality is quantified.

FirstOrderEqualityWithVariable - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents the comparison of two classifier applications.

FirstOrderEqualityWithVariable(boolean, FirstOrderVariable, FirstOrderVariable) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithVariable

Initializing constructor.

FirstOrderEqualityWithVariable(boolean, FirstOrderVariable, FirstOrderVariable, EqualityArgumentReplacer) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithVariable

This constructor specifies a variable setter for when this equality is quantified.

FirstOrderImplication - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents an implication between two first order constraints.

FirstOrderImplication(FirstOrderConstraint, FirstOrderConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderImplication

Initializing constructor.

FirstOrderNAryConstraint - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents a first order constraint with an arbitrary number of arguments, usually assumed to be greater than or equal to 2.

FirstOrderNAryConstraint() - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNAryConstraint

Default constructor.

FirstOrderNegation - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents the negation operator applied to a first order constraint.

FirstOrderNegation(FirstOrderConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNegation

Initializing constructor.

FirstOrderVariable - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents a classifier application.

FirstOrderVariable(Learner, Object) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderVariable

Initializing constructor.

FLOAT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

FLOAT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Value of the type variable.

flush() - Method in class edu.illinois.cs.cogcomp.lbjava.io.ChannelOutputStream

Forces any buffered output bytes to be written to ChannelOutputStream.channel.

flush() - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexOutputStream

Flushes this output stream and forces any buffered output bytes to be written out.

fold - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Keeps track of the current fold; used only in manual splitting.

FoldParser - Class in edu.illinois.cs.cogcomp.lbjava.parse

Useful when performing k-fold cross validation, this parser filters the examples coming from another parser.

FoldParser(Parser, int, FoldParser.SplitPolicy, int, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Constructor for when you don't know how many examples are in the data.

FoldParser(Parser, FoldParser.SplitPolicy, int, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Constructor for when you know neither how many examples are in the data nor K, i.e., how many folds are in the data.

FoldParser(Parser, int, FoldParser.SplitPolicy, int, boolean, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Full constructor.

FoldParser.SplitPolicy - Class in edu.illinois.cs.cogcomp.lbjava.parse

Immutable type representing the way in which examples are partitioned into folds.

FoldSeparator - Class in edu.illinois.cs.cogcomp.lbjava.parse

This is a dummy class which is only used to signify the separation between folds for use in the cross validation method.

FOR - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

FORALL - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

forget() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Clears weakLearners and alpha, although this is not necessary since learn(Object[]) will overwrite them fresh each time it is called.

forget() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reinitializes the learner to the state it started at before any learning was performed.

forget() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Resets the weight vector to associate the default weight with all features.

forget() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Clears the network.

forget() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Clears the network.

forget() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Resets the weight vector to all zeros.

forget() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Reinitializes the learner to the state it started at before any learning was performed.

forget() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Clears the network.

forget() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Clears the network.

forget() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Resets the weight vector to all zeros.

forget() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Resets the internal bookkeeping.

forget() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Destroys the learned version of the WEKA classifier and empties the WekaWrapper.instances collection of examples.

format(double, int) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats a floating point number so that it is rounded and zero-padded to the given number of significant digits after the decimal point.

ForStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a for loop.

ForStatement(ExpressionList, Expression, ExpressionList, Statement, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

Full constructor.

ForStatement(VariableDeclaration, Expression, ExpressionList, Statement, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

Full constructor.

FPMIN - Static variable in class edu.illinois.cs.cogcomp.lbjava.util.StudentT

A small number close to the smallest representable floating point number.

freshClassifier - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Stores a fresh instance of the WEKA classifier for the purposes of forgetting.

FROM - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

FROM - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Value of the type variable.

fromArray() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Determines if this feature comes from an array.

fromArray() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Determines if this feature comes from an array.

fromArray() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Determines if this feature comes from an array.

fromArray() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Determines if this feature comes from an array.

fromArray() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Determines if this feature comes from an array.

fromClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Counts the number of from clauses for error detection.

fromPivot - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Whether examples will come from the pivot fold or not.

FVector - Class in edu.illinois.cs.cogcomp.lbjava.util

This class implements an expandable array of features that should be faster than java's Vector.

FVector() - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.FVector

Constructs a new vector with capacity equal to FVector.defaultCapacity.

FVector(int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.FVector

Constructs a new vector with the specified capacity.

FVector(Feature[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.FVector

Constructs a new vector using the specified array as a starting point.

FVector(FVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.FVector

Constructs a copy of a vector starting with capacity equal to that vector's size.

G

gamma(double) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.StudentT

Gamma function, Lanczos approximation (6 terms)

generateBoundedQuantifier(QuantifiedConstraintExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

AtLeastQuantifierExpressions and AtMostQuantifierExpressions generate their code through this method.

generatedSourceDirectory - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

The directory in which to write generated Java source files (with subdirectories mimicing the package name included).

generateHashingMethods(PrintStream, String) - Static method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Generates the equals(Object) method, which evaluates to true whenever the two objects are of the same type.

generateHeader(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Generates package and import statements from the names in the member variable imported.

generateLearnerBody(PrintStream, LearningClassifierExpression) - Static method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Generate the code that overrides certain methods of Learner to check types and call themselves on the unique instance; also declares other methods and fields of the classifier's implementation.

GenerateParserAndSymbols - Class in edu.illinois.cs.cogcomp.lbjava.frontend

A wrapper for running Main to generate the parser and sym classes, as well as SymbolNames.

GenerateParserAndSymbols() - Constructor for class edu.illinois.cs.cogcomp.lbjava.frontend.GenerateParserAndSymbols

generateTypeChecking(String, String, String, boolean, String, int, String, boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Generates the code appearing at the beginning of, for example, many classifiers' Classifier.classify(Object) methods that checks to see if that input Object has the appropriate type.

generatingClassifier - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

The name of the LBJava classifier that produced this feature.

get(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ScoreSet

Returns the double precision score for a particular classification value.

get(String, Object) - Static method in class edu.illinois.cs.cogcomp.lbjava.infer.InferenceManager

Retrieves the Inference object whose fully qualified name and head object are specified.

get(ClassifierName) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Retrieves the type associated with the given name.

get(Name) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Retrieves the type associated with the given name.

get(String) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Retrieves the type associated with the given name.

get(int) - Method in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

Retrieves the child at the specified index in the vector.

get(int) - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Retrieves the value stored at the specified index of the vector, or null if the vector isn't long enough.

get(int, Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Retrieves the value stored at the specified index of the vector or d if the vector isn't long enough.

getAllClasses() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Returns the set of all classes reported as either predictions or labels.

getAllowableValues() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

getAlpha() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Sigmoid

Retrieves the value of Sigmoid.alpha.

getAlpha() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Softmax

Retrieves the value of Softmax.alpha.

getArgumentKey(Feature, Lexicon, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

A helper method for DiscreteConjunctiveFeature.getFeatureKey(Lexicon,boolean,int), this method computes the feature keys corresponding to the arguments of the conjunction.

getArgumentKey(Feature, Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

A helper method for RealConjunctiveFeature.getFeatureKey(Lexicon,boolean,int), this method computes the feature keys corresponding to the arguments of the conjunction.

getArrayIndex() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Returns the array index of this feature.

getArrayIndex() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Returns the array index of this feature.

getArrayIndex() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Returns the array index of this feature.

getArrayIndex() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Returns the array index of this feature.

getArrayLength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Returns the length of the feature array that this feature comes from.

getArrayLength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Returns the length of the feature array that this feature comes from.

getArrayLength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Returns the length of the feature array that this feature comes from.

getArrayLength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Returns the length of the feature array that this feature comes from.

getAveragedWeight(int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Returns the averaged weight of the given feature.

getBaseLTU() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

getBeta() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Returns the current value of the BinaryMIRA.beta member variable.

getBeta() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Returns the current value of the SparseWinnow.beta variable.

getBias() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

getBooleanValue(int) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

When the problem has been solved, use this method to retrieve the value of any Boolean inference variable.

getBound() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifierArgumentReplacer

Computes the new value of the bound.

getBoundType(int) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Returns the type of the specified constraint's bound.

getByte(int) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Returns the byte at index i of ByteString.value.

getByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Retrieves this feature's identifier as a byte string.

getByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Retrieves this feature's identifier as a byte string.

getByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Retrieves this feature's identifier as a byte string.

getByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Retrieves this feature's identifier as a byte string.

getByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Retrieves this feature's identifier as a byte string.

getByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Retrieves this feature's identifier as a byte string.

getByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Retrieves this feature's identifier as a byte string.

getByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Retrieves this feature's identifier as a byte string.

getByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Retrieves this feature's identifier as a byte string.

getByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Retrieves this feature's identifier as a byte string.

getByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Retrieves this feature's identifier as a byte string.

getByteStringValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Gives a string representation of the value of this feature.

getByteStringValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Gives a string representation of the value of this feature.

getByteStringValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Gives a string representation of the value of this feature.

getByteStringValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Gives a string representation of the value of this feature.

getByteStringValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Gives a string representation of the value of this feature.

getByteStringValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealFeature

Gives a string representation of the value of this feature.

getChildFeature(Feature, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

This method adds the given feature to this lexicon and also recursively adds its children, if any.

getChildFeature(Feature, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Used to lookup the children of conjunctive and referring features during training, this method checks Lexicon.lexiconChildren if the feature isn't present in Lexicon.lexicon and Lexicon.lexiconInv, and then stores the given feature in Lexicon.lexiconChildren if it wasn't present anywhere.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Constraint

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderBinaryConstraint

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConstant

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEquality

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNAryConstraint

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNegation

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalBinaryConstraint

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNAryConstraint

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifiedConstraintInvocation

Returns the children of this constraint in an array.

getChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Quantifier

Returns the children of this constraint in an array.

getClass(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieves the Class object with the given name.

getClass(String, boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieves the Class object with the given name.

getClassifier() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderVariable

Retrieves the classifier.

getClassifier() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Retrieves the classifier.

getClassifier(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve a Classifier by name using the no-argument constructor.

getClassifier(String, boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve a Classifier by name using the no-argument constructor.

getClassifier(String, Class[], Object[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve a Classifier by name using a constructor with arguments.

getClassifier(String, Class[], Object[], boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve a Classifier by name using a constructor with arguments.

getCollection() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifierArgumentReplacer

Computes the new collection.

getCompositeChildren() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

If this classifier is a composite generator, this method will be overridden such that it returns all the classifiers it calls on in a list.

getConfidence() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Returns the current value of the SparseConfidenceWeighted.confidence variable.

getConstantLearningRate() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Getter - get the constant learning rate

getConstraintBound(int) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Returns the bound of the specified constraint.

getConstraintCoefficient(int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Returns the specified constraint coefficient.

getConstructor(String, Class[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve the constructor of the given class with the given parameter types.

getConstructor(String, String[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve the constructor of the given class with the given parameter type names.

getConstructor(String, String[], boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve the constructor of the given class with the given parameter type names.

getConstructor(String, Class[], boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve the constructor of the given class with the given parameter types.

getCorrect(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Returns the number of times the requested prediction was reported correctly.

getCount() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Count

Returns the integer count.

getCount(int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Returns the count of the given feature.

getCountPolicy() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Returns the feature counting policy currently employed by this lexicon.

getCurrentLexicon() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the feature lexicon in memory, rather than reading from disk

getCutoff() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Returns the value of Lexicon.pruneCutoff, or Lexicon.size() if Lexicon.pruneCutoff is -1.

getDistribution(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Returns a discrete distribution of the classifier's prediction values.

getEncoding() - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Returns the name of the encoding method of this byte string.

getExample() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderVariable

Retrieves the example object.

getExample() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Retrieves the example object.

getExampleArray(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Converts an example object into an array of arrays representing the example including its labels.

getExampleArray(Object, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Converts an example object into an array of arrays representing the example.

getExamples() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Returns the SparseAveragedPerceptron.AveragedWeightVector.examples variable.

getExamples() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayParser

Returns the value of ArrayParser.examples.

getExtractor() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the extractor.

getF(double, String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Returns the F_beta score associated with the given label.

getF1(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Returns the F₁ score associated with the given label.

getFeature(int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns the feature at the specified index.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Return the feature that should be used to index this feature into a lexicon.

getFeatureKey(Lexicon, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Return the feature that should be used to index this feature into a lexicon.

getFinal() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Argument

Retrieves the value of the isFinal member variable.

getFindersLength() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

Retrieves the number of head finder types.

getFinderType(int) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

Retrieves the type of the i^th head finder object.

getFirst() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Returns the first element of the list.

getGeneratingClassifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Retrieves the name of the classifier that produced this feature.

getHead() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Retrieves the head object.

getHead() - Method in exception edu.illinois.cs.cogcomp.lbjava.infer.InferenceNotOptimalException

Retrieves the head object, InferenceNotOptimalException.head.

getHeadFinderTypes() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Returns the fully qualified names of the types of objects for which head finder methods have been defined.

getHeadType() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Returns the fully qualified name of the type of the head object for this inference.

getHeadType() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

Retrieves the value of the headType variable.

getInitialVariance() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Returns the current value of the SparseConfidenceWeighted.initialVariance variable.

getInitialWeight() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Returns the current value of the LinearThresholdUnit.initialWeight variable.

getInput() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

Retrieves the value of the input variable.

getInputType() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Returns a string describing the input type of this classifier.

getInputType() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVectorReturner

Returns a string describing the input type of this classifier.

getInputType() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.LabelVectorReturner

Returns a string describing the input type of this classifier.

getInputType() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ValueComparer

Returns a string describing the input type of this classifier.

getIntegerValue(int) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

getIsTraining() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Returns the value of the static isTraining flag inside BatchTrainer.learner's runtime class.

getK() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Retrieves the value of FoldParser.K, which may have been computed in the constructor if the splitting policy is manual.

getLabel(int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns the label at the specified index.

getLabeled(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Returns the number of times the requested label was reported.

getLabeler() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the labeler.

getLabelLexicon() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the label lexicon.

getLabels() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Returns the set of labels that have been reported so far.

getLearner(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve a Learner by name using the no-argument constructor.

getLearner(String, boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve a Learner by name using the no-argument constructor.

getLearner(String, Class[], Object[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve a Learner by name using a constructor with arguments.

getLearner(String, Class[], Object[], boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve a Learner by name using a constructor with arguments.

getLearningRate() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Returns the original value of the LinearThresholdUnit.learningRate variable.

getLearningRate() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Returns the current value of the LinearThresholdUnit.learningRate variable.

getLearningRate() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Returns the current value of the LinearThresholdUnit.learningRate variable.

getLearningRate() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Returns the current value of the StochasticGradientDescent.learningRate variable.

getLeft() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Returns the value of DiscreteConjunctiveFeature.left.

getLeft() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Returns the value of RealConjunctiveFeature.left.

getLeftObject() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.EqualityArgumentReplacer

Computes the object on the left hand side of the equality.

getLeftValue() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.EqualityArgumentReplacer

Computes the value on the left hand side of the equality.

getLexicon() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the feature lexicon.

getLexiconDiscardCounts() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns this learner's feature lexicon after discarding any feature counts it may have been storing.

getLexiconLocation() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the lexicon's location.

getLine() - Method in interface edu.illinois.cs.cogcomp.lbjava.CodeGenerator

Returns the line number on which this AST node is found in the source (starting from line 0).

getLine() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpression

Returns the line number on which this AST node is found in the source (starting from line 0).

getLine() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintDeclaration

Returns the line number on which this AST node is found in the source (starting from line 0).

getLine() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Returns the line number on which this AST node is found in the source (starting from line 0).

getLog() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Count

Returns the log after updating it.

getLossFunction() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Getter - get loss function

getLTU(int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

returns the i-th LTU; the type of this depends on the type of the baseLTU (see above).

getM() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Returns the value of m.

getMap() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Simply returns the map stored in Lexicon.lexicon.

getMaximize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Returns true iff the objective function is to be maximized.

getMethodBody() - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Gives access to the TranslateToJava.methodBody member variable so that this pass can be invoked selectively on some subset of a method body.

getModelLocation() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the model's location.

getName() - Method in interface edu.illinois.cs.cogcomp.lbjava.CodeGenerator

Returns the name of the code generator.

getName() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Argument

Retrieves the name portion of the argument.

getName() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpression

Returns the name of the ClassifierExpression.

getName() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintDeclaration

Returns the name of the ConstraintDeclaration.

getName() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Returns the name of the InferenceDeclaration.

getName() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReferenceType

Returns the name of the class that defines this type.

getName() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Accuracy

Returns the name of the testing metric.

getName() - Method in interface edu.illinois.cs.cogcomp.lbjava.learn.TestingMetric

Returns the name of the testing metric.

getNegativeThickness() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Returns the current value of the LinearThresholdUnit.negativeThickness variable.

getNetwork() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

getNormalizer(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Returns the normalization function associated with the given classifier in this inference.

getNumClasses() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

getNumExamples() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

getNumExamples() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

Returns the number of examples left in the example file.

getNumFeatures() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

getObjectiveCoefficient(int) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Returns the specified objective coefficient.

getOutput() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

Retrieves the value of the input variable.

getOutputType() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Returns a string describing the output feature type of this classifier.

getOutputType() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVectorReturner

Returns a string describing the output type of this classifier.

getOutputType() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.LabelVectorReturner

Returns a string describing the output type of this classifier.

getOutputType() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Returns a string describing the output feature type of this classifier.

getOutputType() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner

This learner's output type is "discrete%".

getOutputType() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Returns a string describing the output feature type of this classifier.

getOutputType() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

This learner's output type is "mixed%".

getOverallStats() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Computes overall the overall statistics precision, recall, F₁, and accuracy.

getOverallStats(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Computes overall the overall statistics precision, recall, F_beta, and accuracy.

getPackage() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Retrieves this feature's package.

getPackage() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Gets the package name.

getParameterName() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Returns the value of ParameterSet.parameterName.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Retrieves the parameters that are set in this learner.

getParameters() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Retrieves the parameters that are set in this learner.

getParent() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Retrieves the parent of this table.

getParser() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Returns the value of BatchTrainer.parser.

getParser() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Returns the value of FoldParser.parser.

getParser(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve a Parser by name using the no-argument constructor.

getParser(String, boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve a Parser by name using the no-argument constructor.

getParser(String, Class[], Object[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve a Parser by name using a constructor with arguments.

getParser(String, Class[], Object[], boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ClassUtils

Retrieve a Parser by name using a constructor with arguments.

getPercentage() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

Returns the value of Lexicon.PruningPolicy.percentage.

getPivot() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Returns the value of FoldParser.pivot.

getPlatformIndependentFilePath(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.FileUtils

Update FilePath separator for file paths read from pom.xml config.

getPositiveThickness() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Returns the current value of the LinearThresholdUnit.positiveThickness variable.

getPrecedence() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Produces the precedence of this operator.

getPrecision(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Returns the precision associated with the given prediction.

getPredicted(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Returns the number of times the requested prediction was reported.

getPrediction() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Retrieves the prediction.

getPredictions() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Returns the set of predictions that have been reported so far.

getPrior() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Returns the prior count of the prediction value associated with this vector.

getProgressOutput() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Returns the value of BatchTrainer.progressOutput.

getPrunedLexiconSize() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the size of the lexicon after any pruning that may have taken place or 0 if the lexicon's location isn't known.

getRealValue(int) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

getRecall(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Returns the recall associated with the given label.

getReferent() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Returns the value of DiscreteReferrer.referent.

getReferent() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Returns the value of RealReferrer.referent.

getRight() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Returns the value of DiscreteConjunctiveFeature.right.

getRight() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Returns the value of RealConjunctiveFeature.right.

getRightObject() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.EqualityArgumentReplacer

Computes the object on the right hand side of the equality.

getRightValue() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.EqualityArgumentReplacer

Computes the value on the right hand side of the equality.

getScore(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ScoreSet

Retrieves the Score object associated with the given classification value.

getScore() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderVariable

Retrieves the score of the current value of this variable.

getScores() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderVariable

Retrieves all the scores for the values this variable may take.

getSeparator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List

Returns the separating characters.

getSolver() - Method in exception edu.illinois.cs.cogcomp.lbjava.infer.InferenceNotOptimalException

Retrieves the ILP problem instance, InferenceNotOptimalException.solver.

getSolverType(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine.Parameters

Converts the string representation of the solver type into a liblinear.SolverType object to be used by liblinear during training.

getSortedMap(int[], double[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns a sorted map where the key is the feature index and the value is the feature value.

getStrength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Returns the strength of this feature if it were to be placed in a mathematical vector space.

getStrength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

Returns the strength of this feature if it were to be placed in a mathematical vector space.

getStrength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Returns the strength of this feature if it were to be placed in a mathematical vector space.

getStrength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Returns the strength of this feature if it were to be placed in a mathematical vector space.

getStrength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Returns the strength of this feature if it were to be placed in a mathematical vector space.

getStrength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Returns the strength of this feature if it were to be placed in a mathematical vector space.

getStrength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Simply returns the value of RealPrimitiveFeature.value.

getStrength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Simply returns the value of RealPrimitiveStringFeature.value.

getStrength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Simply returns the strength of RealReferrer.referent.

getStrength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Simply returns the strength of RealReferrer.referent.

getStrength() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Simply returns the strength of RealReferrer.referent.

getStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Retrieves this feature's identifier as a string.

getStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Retrieves this feature's identifier as a string.

getStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Retrieves this feature's identifier as a string.

getStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Retrieves this feature's identifier as a string.

getStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Retrieves this feature's identifier as a string.

getStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Retrieves this feature's identifier as a string.

getStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Retrieves this feature's identifier as a string.

getStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Retrieves this feature's identifier as a string.

getStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Retrieves this feature's identifier as a string.

getStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Retrieves this feature's identifier as a string.

getStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Retrieves this feature's identifier as a string.

getStringValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Gives a string representation of the value of this feature.

getStringValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Gives a string representation of the value of this feature.

getStringValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Gives a string representation of the value of this feature.

getStringValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Gives a string representation of the value of this feature.

getStringValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Gives a string representation of the value of this feature.

getStringValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealFeature

Gives a string representation of the value of this feature.

getSymbols() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Returns the names of the symbols in this (local) table.

getThreshold(int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

Returns the value of the i^th threshold in Lexicon.PruningPolicy.thresholds when in "Percentage" mode, but ignores the parameter i and returns the first element of Lexicon.PruningPolicy.thresholds when in "Absolute" mode.

getThreshold() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Returns the current value of the LinearThresholdUnit.threshold variable.

getType() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Argument

Retrieves the type portion of the argument.

getType() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

Returns the type of the declaration.

getType() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintDeclaration

Returns the type of the declaration.

getType() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Declaration

Returns the type of the declaration.

getType() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportDeclaration

Returns null, since this method should never be called on an object of this class.

getType() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Returns the type of the declaration.

getType() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PackageDeclaration

Returns null, since this method should never be called on an object of this class.

getTypeName() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Retrieves the name of the base type represented by this object.

getValue() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderVariable

Retrieves the value this variable currently takes.

getValueIndex() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

Returns the index in the generating classifier's value list of this feature's value.

getValueIndex() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Returns the index in the generating classifier's value list of this feature's value.

getVariable(PropositionalVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Retrieves the requested variable, creating it first if it doesn't yet exist.

getVariable(FirstOrderVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Retrieves the requested variable, creating it first if it doesn't yet exist.

getVariableTypes() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AtLeastQuantifierExpression

Returns a set of Arguments storing the name and type of each variable that is a subexpression of this expression.

getVariableTypes() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AtMostQuantifierExpression

Returns a set of Arguments storing the name and type of each variable that is a subexpression of this expression.

getVariableTypes() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

Returns a set of Arguments storing the name and type of each variable that is a subexpression of this expression.

getVariableTypes() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintExpression

Returns a set of Arguments storing the name and type of each variable that is a subexpression of this expression.

getVariableTypes() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintInvocation

Returns a set of Arguments storing the name and type of each variable that is a subexpression of this expression.

getVariableTypes() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintStatementExpression

Returns a set of Arguments storing the name and type of each variable that is a subexpression of this expression.

getVariableTypes() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Expression

Returns a set of Arguments storing the name and type of each variable that is a subexpression of this expression.

getVariableTypes() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList

Returns a set of Arguments storing the name and type of each variable that is a subexpression of this expression.

getVariableTypes() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Returns a set of Arguments storing the name and type of each variable that is a subexpression of this expression.

getVariableTypes() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Name

Returns a set of Arguments storing the name and type of each variable that is a subexpression of this expression.

getVariableTypes(boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Name

Returns a set of Arguments storing the name and type of each variable that is a subexpression of this expression.

getVariableTypes() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.QuantifiedConstraintExpression

Returns a set of Arguments storing the name and type of each variable that is a subexpression of this expression.

getWeight() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns the value of FeatureVector.weight.

getWeight(int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Returns the weight of the given feature

getWeight(int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

Returns the double precision value for the given feature, or sets a random one and returns it if one did not already exist.

getWeight(int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Returns the weight of the given feature.

getWeight(int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Returns the weight of the given feature.

getWeights() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

getWeightVector() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Getter - get weight vector

getWeightVector() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

global - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.CountPolicy

Represents global counting.

globalSymbolTable - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.AST

The symbolTable variable mirrors this variable.

goldHistogram - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

The histogram of correct labels.

goldStats - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.TestReal

goldSubtractPredictionAbsoluteStats - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.TestReal

goldSubtractPredictionStats - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.TestReal

GOTO - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

GREATER_THAN - Static variable in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Represents the constraint type "greater than or equal to".

GREATER_THAN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

GREATER_THAN_OR_EQUAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

groups - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

(¬ø) The list of labeled blocks of statements, if any.

GT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

GTEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

H

handleEncodingException(Exception) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Handles exceptions generated by unsupported encodings.

hasByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Determines if this feature contains a byte string identifier field.

hasByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Determines if this feature contains a byte string identifier field.

hasByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Determines if this feature contains a byte string identifier field.

hasByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Determines if this feature contains a byte string identifier field.

hasByteStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Determines if this feature contains a byte string identifier field.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

The hash code of a DiscreteArrayFeature is the sum of the hash codes of the containing package, the identifier, the value and the array index.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

The hash code of a DiscreteArrayStringFeature is the sum of the hash codes of the containing package, the identifier, the value and the array index.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Returns a hash code based on the hash codes of DiscreteConjunctiveFeature.left and DiscreteConjunctiveFeature.right.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

The hash code of a DiscretePrimitiveFeature is the sum of the hash codes of its containing package, identifier, and value.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

The hash code of a DiscretePrimitiveStringFeature is the sum of the hash codes of its containing package, identifier, and value.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

The hash code of a DiscreteReferrer is the sum of the hash codes of its containing package, identifier, and the referent feature.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

The hash code of a DiscreteReferringFeature is the sum of the hash codes of its containing package, identifier, and the referent feature.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

The hash code of a DiscreteReferringStringFeature is the sum of the hash codes of its containing package, identifier, and the referent feature.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

The hash code of a Feature is a function of the hash codes of Feature.containingPackage and Feature.generatingClassifier.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

The hash code for a FeatureVector is simply the sum of the hash codes of the features and the labels.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

The hash code of a RealArrayFeature is the sum of the hash codes of the containing package, the identifier, the value, and the array index.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

The hash code of a RealArrayStringFeature is the sum of the hash codes of the containing package, the identifier, the value, and the array index.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Returns a hash code based on the hash codes of RealConjunctiveFeature.left and RealConjunctiveFeature.right.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

The hash code of a RealPrimitiveFeature is the sum of the hash codes of the containing package, the identifier, and the value.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

The hash code of a RealPrimitiveStringFeature is the sum of the hash codes of the containing package, the identifier, and the value.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

The hash code of a RealReferrer is the sum of the hash codes of the containing package, the identifier, and the referent feature.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

The hash code of a RealReferringFeature is the sum of the hash codes of the containing package, the identifier, and the referent feature.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

The hash code of a RealReferringStringFeature is the sum of the hash codes of the containing package, the identifier, and the referent feature.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.AtLeastQuantifier

The hash code of a AtLeastQuantifier is the sum of the hash codes of its children plus one.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.AtMostQuantifier

The hash code of a AtMostQuantifier is the sum of the hash codes of its children.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ExistentialQuantifier

The hash code of a ExistentialQuantifier is the sum of the hash codes of its children plus one.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConjunction

The hash code of a FirstOrderConjunction is the sum of the hash codes of its children plus one.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConstant

The hash code of a FirstOrderConstant is the hash code of the Boolean object formed from the constant.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDisjunction

The hash code of a FirstOrderDisjunction is the sum of the hash codes of its children.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDoubleImplication

The hash code of a FirstOrderDoubleImplication is the sum of the hash codes of its children plus three.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityTwoValues

The hash code of a FirstOrderEqualityTwoValues is the sum of the hash codes of its children.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithValue

The hash code of a FirstOrderEqualityWithValue is the sum of the hash codes of its children plus 1.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithVariable

The hash code of a FirstOrderEqualityWithVariable is the sum of the hash codes of its children plus 2.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderImplication

The hash code of a FirstOrderImplication is the sum of the hash codes of its children plus two.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNegation

The hash code of a FirstOrderNegation is the hash code of its child constraint plus 1.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderVariable

The hash code of a FirstOrderVariable is the hash code of the string representation of the classifier plus the system's hash code for the example object.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Simply returns the head's hash code.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

The hash code of a PropositionalAtLeast is the sum of the hash codes of its children plus two.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

The hash code of a PropositionalConjunction is the sum of the hash codes of its children plus one.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

The hash code of a PropositionalConstant is the hash code of the Boolean object formed from the constant.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

The hash code of a PropositionalDisjunction is the sum of the hash codes of its children.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

The hash code of a PropositionalDoubleImplication is the sum of the hash codes of its children plus three.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

The hash code of a PropositionalImplication is the sum of the hash codes of its children plus two.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

The hash code of a PropositionalNegation is the hash code of its child constraint plus 1.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

The hash code of a PropositionalVariable is the hash code of the string representation of the classifier plus the system's hash code for the example object plus the hash code of the prediction.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifiedConstraintInvocation

The hash code of a QuantifiedConstraintInvocation is the sum of the hash codes of its children.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Quantifier

The hash code of a Quantifier is the sum of the hash codes of its children plus three.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.UniversalQuantifier

The hash code of a UniversalQuantifier is the sum of the hash codes of its children.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Argument

The hash code of an Argument is simply the hash code of its name.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayCreationExpression

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayInitializer

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayType

A hash code based on the hash code of ArrayType.type.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AssertStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Assignment

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryExpression

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Block

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BreakStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CastExpression

A hash code based on the hash codes of CastExpression.type and CastExpression.expression.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchClause

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierCastExpression

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierName

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

A hash code based on ClassifierReturnType.type.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

A hash code based on the hash code of ClassifierType.input.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CodedClassifier

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CompositeGenerator

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conditional

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conjunction

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Constant

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

A hash code based on the hash codes of the elements of the list.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ContinueStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.EmptyStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.FieldAccess

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.IfStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.IncrementExpression

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceInvocation

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

A hash code based on the hash code of InferenceType.headType.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InstanceofExpression

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LabeledStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List

A hash code based on the hash codes of the elements of the list.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Name

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NormalizerType

Returns a constant, since all objects of this type are equal according to NormalizerType.equals(Object).

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

A hash code based on the hash codes of the constituent expressions.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

A hash code based on PrimitiveType.type.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReferenceType

A hash code based on the hash code of ReferenceType.name.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReturnStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SubscriptVariable

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroup

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabel

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SynchronizedStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ThrowStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.TryStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.UnaryExpression

Returns a hash code value for java hash structures.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.WhileStatement

Returns a hash code for this ASTNode.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Returns a hash code for this lexicon.

hashCode - Variable in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

The hash code of the String decoding of this byte string.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Returns a hash code for this object.

hashCode() - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

A hash code based on the hash code of FVector.vector.

hasNext() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNodeIterator

Determines whether there are any child nodes left to be accessed.

hasNext() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List.NodeListIterator

Returns true if this list iterator has more elements when traversing the list in the forward direction.

hasNulls() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Returns true iff there exist "null" labels.

hasPrevious() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List.NodeListIterator

Returns true if this list iterator has more elements when traversing the list in the reverse direction.

hasStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Determines if this feature contains a string identifier field.

hasStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Determines if this feature contains a string identifier field.

hasStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Determines if this feature contains a string identifier field.

hasStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Determines if this feature contains a string identifier field.

hasStringIdentifier() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Determines if this feature contains a string identifier field.

HEAD - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

head - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Objects of this class are differentiated by their "head" objects.

head - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

(¬ø) A specification of the object from which all variables can be found.

HEAD_FINDER - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.Clause

Value of the type variable.

HeadFinder(Argument, Block) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.HeadFinder

Full constructor.

headFinders - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

(¬ø) The methods used to find the head object given objects of different types.

headFinderTypes - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

The types of the head finder objects.

headType - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

The type of the head object.

HexInputStream - Class in edu.illinois.cs.cogcomp.lbjava.io

This class receives input from another InputStream assuming that data is little endian, hexidecimal text, converts that text to bytes, and makes those bytes available through its interface.

HexInputStream(InputStream) - Constructor for class edu.illinois.cs.cogcomp.lbjava.io.HexInputStream

Initializes this stream with another input stream.

HexOutputStream - Class in edu.illinois.cs.cogcomp.lbjava.io

This class will convert whatever data is sent to it into little endian, hexidecimal text and send that text on to another OutputStream.

HexOutputStream(OutputStream) - Constructor for class edu.illinois.cs.cogcomp.lbjava.io.HexOutputStream

Initializes this stream with another output stream.

HexStringInputStream - Class in edu.illinois.cs.cogcomp.lbjava.io

Behaves the same as HexInputStream, except its constructor takes a String as input to read.

HexStringInputStream(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.io.HexStringInputStream

Initializes this stream with another input stream.

highScoreValue() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ScoreSet

Retrieves the value with the highest score in this set.

histogramAdd(HashMap, String, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Takes a histogram implemented as a map and increments the count for the given key by the given amount.

histogramAddAll(HashMap, HashMap) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Takes two histograms implemented as maps and adds the amounts found in the second histogram to the amounts found in the first.

histogramGet(HashMap, String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Takes a histogram implemented as a map and retrieves the count for the given key.

I

I - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.List.NodeListIterator

An iterator into list.

ID - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

The identification number for this object, used in debug file names.

identifier - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

The identifier string distinguishes this Feature from other Features.

identifier - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

The identifier string distinguishes this Feature from other Features.

identifier - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

The identifier string distinguishes this Feature from other Features.

identifier - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

The identifier string distinguishes this Feature from other Features.

identifier - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

The identifier string distinguishes this Feature from other Features.

identifier - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

The identifier string distinguishes this Feature from other Features.

identifier - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

The identifier string distinguishes this Feature from other Features.

identifier - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

The identifier string distinguishes this Feature from other Features.

IDENTIFIER - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

IdentityNormalizer - Class in edu.illinois.cs.cogcomp.lbjava.learn

This Normalizer simply returns the same ScoreSet it was passed as input without modifying anything.

IdentityNormalizer() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.IdentityNormalizer

IF - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

IfStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents an if statement.

IfStatement(Expression, Statement, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.IfStatement

Initializing constructor.

IfStatement(Expression, Statement, Statement, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.IfStatement

Full constructor.

ILPInference - Class in edu.illinois.cs.cogcomp.lbjava.infer

This class employs an ILPSolver to solve a constrained inference problem.

ILPInference() - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Don't use this constructor, since it doesn't set an ILP algorithm.

ILPInference(ILPSolver) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Initializes the ILP algorithm, but not the head object.

ILPInference(ILPSolver, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Initializes the ILP algorithm, but not the head object.

ILPInference(Object) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Don't use this constructor, since it doesn't set an ILP algorithm.

ILPInference(Object, ILPSolver) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Sets the head object and the ILP algorithm.

ILPInference(Object, ILPSolver, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Sets the head object and the ILP algorithm.

IMPLEMENTS - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

IMPLICATION - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

IMPLICATION - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

IMPORT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

ImportDeclaration - Class in edu.illinois.cs.cogcomp.lbjava.IR

Representation of an import declaration.

ImportDeclaration(Name, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ImportDeclaration

Full constructor.

importedSize() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Returns the size of the list of imported items.

ImportList - Class in edu.illinois.cs.cogcomp.lbjava.IR

Currently, this is just a wrapper class for LinkedList.

ImportList() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ImportList

Default constructor.

ImportList(ImportDeclaration) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ImportList

Initializing constructor.

ImportList.ImportListIterator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Used to iterate though the children of a list of AST nodes.

ImportListIterator() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ImportList.ImportListIterator

imports - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.AST

(¬ø) The list of import statements at the top of the source file.

IN - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

in - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

Reader for file currently being parsed.

in - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.LineByLine

Reader for file currently being parsed.

includePruned - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

Whether the returned example arrays should include pruned features.

increment(PropositionalConstraint[][], int[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Utility method for iterating through all combinations of constraint children.

increment - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

The factor to increment by.

increment(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Count

Increments the count, but does not update the log.

increment(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Changes state to reflect retrieval of the next example from the parser.

incrementCount(int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Increments the count of the feature with the given index(es).

incrementCount(int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Increments the count of the given feature.

IncrementExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents both increment and decrement expressions.

IncrementExpression(Operator, Expression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.IncrementExpression

Initializing constructor.

incrementParentCounts(Feature, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Helper method for methods like ChildLexicon.childLexiconLookup(DiscreteConjunctiveFeature,int) that actually does the work of looking up the child feature and updating its parent counts.

indentedPrintln(String) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Prints the given text preceded by the amount of indentation called for in the indent member variable and followed by a new line.

indentedPrintln(String, ASTNode) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Prints the given text preceeded by the amount of indentation called for in the indent member variable and followed by the line number and byte offset information for the specified ASTNode and a new line.

index - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNodeIterator

Index into the children array.

index - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayParser

The pointer to the current cell of the ArrayParser.examples array.

indexMap - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Used during ILP constraint generation.

infer() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Uses the provided ILP algorithm to solve the ILP proglem if it hasn't already been solved.

infer() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes implement this method to perform the inference, setting the values of the variables such that they maximize the objective function while satisfying the constraints.

INFERENCE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

Inference - Class in edu.illinois.cs.cogcomp.lbjava.infer

An object of this class keeps track of all the information necessary to perform inference.

Inference() - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Default constructor.

Inference(Object) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Initializes the head object.

inference - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceInvocation

(¬ø) The name of the inference to invoke.

InferenceDeclaration - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents an inference specification.

InferenceDeclaration(String, int, int, Name, Argument, InferenceDeclaration.HeadFinder[], InferenceDeclaration.NormalizerDeclaration[], ConstraintDeclaration, InstanceCreationExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Full constructor.

InferenceDeclaration(TokenValue, TokenValue, Argument, LinkedList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Parser's constructor.

InferenceDeclaration.Clause - Class in edu.illinois.cs.cogcomp.lbjava.IR

An intermediate class used during parsing to represent the various clauses of an inference declaration.

InferenceDeclaration.HeadFinder - Class in edu.illinois.cs.cogcomp.lbjava.IR

A head finder is a method that finds the head object for an inference given another object.

InferenceDeclaration.NormalizerDeclaration - Class in edu.illinois.cs.cogcomp.lbjava.IR

A normalizer declaration is a clause of an inference declaration that specifies a normalizer to be used in association with a particular learning classifier or in general.

InferenceInvocation - Class in edu.illinois.cs.cogcomp.lbjava.IR

An inference can be invoked as a method with the name of a learning classifier involved in that inference as its lone argument.

InferenceInvocation(Name, Name) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InferenceInvocation

Initializing constructor.

InferenceManager - Class in edu.illinois.cs.cogcomp.lbjava.infer

The inference manager is a cache of Inference objects accessed via their names and head objects.

InferenceManager() - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.InferenceManager

InferenceNotOptimalException - Exception in edu.illinois.cs.cogcomp.lbjava.infer

Exceptions of this type are thrown by the ILPInference class when the selected ILPSolver did not successfully find the optimal solution to the inference problem.

InferenceNotOptimalException(ILPSolver, Object) - Constructor for exception edu.illinois.cs.cogcomp.lbjava.infer.InferenceNotOptimalException

Initializing constructor.

InferenceType - Class in edu.illinois.cs.cogcomp.lbjava.IR

An inference's type is defined by the type of the head object as well as the types of objects from which the head can be found.

InferenceType(Type, Type[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

Initializing constructor.

InferenceType(Type, InferenceDeclaration.HeadFinder[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

Initializing constructor.

init_actions() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Action encapsulation object initializer.

initialBias - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

The first value for BiasedWeightVector.bias.

initialize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Quantifier

Makes sure that the enclosingQuantificationSettings vector exists, then adds a place holder for this quantifier's quantification variable setting.

initialize(int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Initializes the weight vector array to the size of the supplied number of features.

initialize(int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

This method is sometimes called before training begins, although it is not guaranteed to be called at all.

initialize(int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Initializes the weight vector array to the size of the specified number of features, setting each weight equal to LinearThresholdUnit.initialWeight.

initialize(int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Initializes the weight vector array to the size of the supplied number of features, with each cell taking the default value of LinearThresholdUnit.initialWeight.

initialize(int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Sets the number of examples and features.

initialize(int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializes the example vector arrays.

initializeAttributes() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Takes attributeString and initializes this wrapper's WekaWrapper.instances collection to take those attributes.

initializer - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayCreationExpression

(ø) Initial values for the new array.

initializer - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

(ø) The variable declaration in the loop header (if any).

initializers - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

(ø) The initializing expression(s) in the loop header (if any).

initializers - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

(¬ø) The initializing expressions for the declared variables, null being an allowable value.

initialVariance - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

The strictly positive initial variance of the parameters; default SparseConfidenceWeighted.defaultInitialVariance.

initialVariance - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted.Parameters

The strictly positive initial variance of the parameters; default SparseConfidenceWeighted.defaultInitialVariance.

initialWeight - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

The weight associated with a feature when first added to the vector; default LinearThresholdUnit.defaultInitialWeight.

initialWeight - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit.Parameters

The weight associated with a feature when first added to the vector; default LinearThresholdUnit.defaultInitialWeight.

input - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

The type of the classifier's input.

inRounds - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

true iff this parameter set appears inside the rounds clause of a LearningClassifierExpression.

insert(LinkedChild, int) - Method in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

Inserts the specified child into the specified index.

InstanceCreationExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents an expression creating a class instance.

InstanceCreationExpression(Name, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InstanceCreationExpression

Initializing constructor.

InstanceCreationExpression(Name, ExpressionList, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InstanceCreationExpression

Initializing constructor.

InstanceCreationExpression(Expression, Name, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InstanceCreationExpression

Initializing constructor.

InstanceCreationExpression(Expression, Name, ExpressionList, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InstanceCreationExpression

Full constructor.

instanceNumber - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

Remembers the instance number of this instance.

INSTANCEOF - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

INSTANCEOF - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

InstanceofExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents an instanceof expression.

InstanceofExpression(Expression, Type, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InstanceofExpression

Full constructor.

instances - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

The main collection of Instance objects.

INT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

INT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Value of the type variable.

INTERFACE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

intersect(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

The intersection of two conjunctions is the set of all terms that are common to both conjunctions; the intersection of a conjunction and some other constraint c is c if c is contained in the conjunction and the empty set otherwise.

intersect(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

The intersection of two disjunctions is the set of all terms that are common to both disjunctions; the intersection of a disjunction and some other constraint c is c if c is contained in the disjunction and the empty set otherwise.

invocation - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintInvocation

(¬ø) The invocation.

InvocationArgumentReplacer - Class in edu.illinois.cs.cogcomp.lbjava.infer

Anonymous inner classes extending this class are instantiated by the code generated by the LBJava compiler when creating QuantifiedConstraintInvocation representations.

InvocationArgumentReplacer(Object[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.InvocationArgumentReplacer

Initializing constructor.

invocationIsQuantified - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintInvocation

Filled in by SemanticAnalysis, this flag is set if invocation contains any quantified variables.

invokedGraph - Static variable in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

The keys of this map are the names of CodeGenerators; the values are HashSets of names of other (not necessarily locally defined) CodeGenerators that are invoked within the CodeGenerator named by the associated key.

IOUtilities - Class in edu.illinois.cs.cogcomp.lbjava.io

IOUtilities() - Constructor for class edu.illinois.cs.cogcomp.lbjava.io.IOUtilities

isAbsolute() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

true iff the policy is absolute thresholding.

isClassifierInvocation - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Filled in by the SemanticAnalysis pass, this variable is set to true iff this invocation represents a classifier invocation.

isConjunctive() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Determines if this feature is conjunctive.

isConjunctive() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Determines if this feature is conjunctive.

isConjunctive() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Determines if this feature is conjunctive.

isContainableIn(ClassifierReturnType) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Determines whether the feature(s) returned by a classifier of this type can become part or all of the features returned by a classifier of the specified type.

isDependentOn(String, String) - Static method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Use this method to determine if one CodeGenerator depends on another either directly or indirectly.

isDiscrete() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

Determines if this feature is discrete.

isDiscrete() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Determines if this feature is discrete.

isDiscrete() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealFeature

Determines if this feature is discrete.

isEvaluateArgument - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Filled in by the SemanticAnalysis pass, this variable is set to true iff this invocation is the argument of a learning classifier expression's evaluate clause.

isField - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierName

Is used to distinguish Classifiers that are defined as fields.

isFinal - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

Whether or not the argument was modified as final.

isLabeled() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Determines whether this vector has any labels.

isLearner() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

Retrieves the value of the learner variable.

isNone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

true iff the policy is no pruning.

isNull(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Determines if a label is treated as a "null" label.

isNumber() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Determines whether this type represents a numerical value (including char), as opposed to a boolean or null.

isPercentage() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

true iff the policy is percentage thresholding.

isPrimitive() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Determines if this feature is primitive.

isPrimitive() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Determines if this feature is primitive.

isPrimitive() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Determines if this feature is primitive.

isPrimitive() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Determines if this feature is primitive.

isPrimitive() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Determines if this feature is primitive.

isPruned(int, Lexicon.PruningPolicy) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Determines if the given feature index should be pruned according to the given pruning policy, which must have its thresholds set already in the case that it represents the "Percentage" policy.

isPruned(int, int, Lexicon.PruningPolicy) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Determines if the given feature index should be pruned according to the given pruning policy, which must have its thresholds set already in the case that it represents the "Percentage" policy.

isRange() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

true iff this parameter set was specified as a range.

isReferrer() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Determines if this feature is a referring feature.

isReferrer() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Determines if this feature is a referring feature.

isReferrer() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Determines if this feature is a referring feature.

isSensedValue - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

The SemanticAnalysis pass will let this MethodInvocation know if it is the immediate value child of a SenseStatement by setting this flag.

isSolved() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Tests whether the problem represented by this ILPSolver instance has been solved already.

isUsingConjunctiveLabels() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

isWholeNumber() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Determines whether this type represents a whole number value (including char), as opposed to a floating point, a boolean, or null.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Argument

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayCreationExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayInitializer

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayType

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AssertStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Assignment

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AST

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNode

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AtLeastQuantifierExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AtMostQuantifierExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryConstraintExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Block

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BreakStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CastExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchClause

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchList

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierCastExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpressionList

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierName

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CodedClassifier

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CompositeGenerator

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conditional

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conjunction

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Constant

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintDeclaration

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintInvocation

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintStatementExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintType

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ContinueStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Declaration

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DeclarationList

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DoStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.EmptyStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.FieldAccess

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.IfStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportList

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.IncrementExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.HeadFinder

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.NormalizerDeclaration

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceInvocation

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InstanceofExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LabeledStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Name

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NameList

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NegatedConstraintExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NormalizerType

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.QuantifiedConstraintExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReferenceType

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReturnStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.StatementList

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SubscriptVariable

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroup

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroupList

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabel

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabelList

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SynchronizedStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ThrowStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.TryStatement

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.UnaryExpression

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

Returns an iterator used to successively access the children of this node.

iterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.WhileStatement

Returns an iterator used to successively access the children of this node.

J

javacArguments - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

Holds command line arguments to be sent to javac when compiling.

JAVADOC_COMMENT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

JAVADOC_END_COMMENT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

K

K - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Dictates how cross-validation divides the training data; used only by the cval clause.

K - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) Represents the integer number of subsets to be used in k-fold cross validation; first argument to cval.

K - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

The total number of folds.

kth - Static variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser.SplitPolicy

Represents the split policy in which every k^th example is part of the same fold.

L

L2NormSquared() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns the square of the magnitude of the feature vector.

L2NormSquared(double[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns the square of the magnitude of the given vector.

label - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.BreakStatement

(ø) The label identifying the loop to break out of, if any.

label - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ContinueStatement

(ø) The label identifying the loop to continue, if any.

label - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LabeledStatement

(¬ø) The label for the statement.

label - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedChild

Space for a label for this linked child.

LabeledStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents any statement with an identifier label.

LabeledStatement(TokenValue, Statement) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.LabeledStatement

Parser's constructor.

LabeledStatement(String, Statement, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.LabeledStatement

Full constructor.

labeler - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.ValueComparer

The classifier whose value will be compared.

labeler - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) The classifier this learning classifier gets its labels from.

labeler - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Stores the classifier used to produce labels.

labelLexicon - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Stores the label Lexicon.

labels - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Stores labels.

labels - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

(¬ø) The trailing list of labels, if any.

labels - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroup

(¬ø) The list of labels labeling this group.

labelsSize() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns the size of just the FeatureVector.labels list.

LabelVectorReturner - Class in edu.illinois.cs.cogcomp.lbjava.classify

This classifier expects a FeatureVector as input, and it returns the contents of its labels list in a new FeatureVector as output.

LabelVectorReturner() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.LabelVectorReturner

Default constructor.

lazyMapCreation() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Various other methods in this class call this method to ensure that Lexicon.lexicon is populated before performing operations on it.

LBRACE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

LBRACEBRACE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

LBRACK - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

lce - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

The expression that specified the learner.

lcFilePath - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Caches the location of this learner's offline binary representation.

LEARN - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

learn(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

This method adds the example object to the array storing the training examples.

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

This method adds the example object to the array storing the training examples.

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

AdaGrad's Learning Function: Each row of feature vector + label feed in as arguments; Update internal parameters; Note: 1.

learn(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Trains the learning algorithm given an object as an example.

learn(FeatureVector) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Trains the learning algorithm given a feature vector as an example.

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Trains the learning algorithm given an example formatted as arrays of feature indices, their values, and the example labels.

learn(Object[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Trains the learning algorithm given many objects as examples.

learn(FeatureVector[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Trains the learning algorithm given many feature vectors as examples.

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

The default training algorithm for a linear threshold unit consists of evaluating the example object with the LinearThresholdUnit.score(Object) method and LinearThresholdUnit.threshold, checking the result of evaluation against the label, and, if they are different, promoting when the label is positive or demoting when the label is negative.

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

The training example is multiplexed to the appropriate Learner(s).

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Trains the learning algorithm given an object as an example.

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

This method works just like LinearThresholdUnit.learn(int[],double[],int[],double[]), except it notifies its weight vector when it got an example correct in addition to updating it when it makes a mistake.

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Updates the means and variances according to the new labeled example.

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Finds the optimal multiplier settings before updating the weight vectors.

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Each example is treated as a positive example for the linear threshold unit associated with the label's value that is active for the example and as a negative example for all other linear threshold units in the network.

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Trains the learning algorithm given an object as an example.

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

This method adds the example's features and labels to the arrays storing the training examples.

learn(int[], double[], int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Since WEKA classifiers cannot learn online, this method causes no actual learning to occur, it simply creates an Instance object from this example and adds it to a set of examples from which the classifier will be built once WekaWrapper.doneLearning() is called.

learner - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

Whether or not the classifier is derived from a learning algorithm.

learner - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.NormalizerDeclaration

(ø) The name of the learner to be normalized.

learner - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

The learning classifier being trained.

Learner - Class in edu.illinois.cs.cogcomp.lbjava.learn

Extend this class to create a new Classifier that learns to mimic one an oracle classifier given a feature extracting classifier and example objects.

Learner() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Learner

This constructor is used by the LBJava compiler; it should never be called by a programmer.

Learner(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Initializes the name.

Learner(String, Classifier) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Constructor for unsupervised learning.

Learner(String, Classifier, Classifier) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Constructor for supervised learning.

learner - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

The learning classifier being trained.

Learner.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Parameters classes are used to hold values for learning algorithm parameters, and all learning algorithm implementations must provide a constructor that takes such an object as input.

learnerClass - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

BatchTrainer.learner's class.

learnerClass - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

The class of Train.TrainingThread.learner.

learnerConstructor - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) Tells this learning classifier how to construct its learning algorithm; argument to with.

learnerDependencies - Variable in class edu.illinois.cs.cogcomp.lbjava.Train

The keys of this map are the names of learners; the values are LinkedLists of the names of the learners that the learner named by the key depends on.

learnerName - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) The name of the learner for this classifier; first argument to with.

learnerParameterBlock - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

A block of statements intended to be used to set learner parameters; used only by the with clause.

learnerParameterBlock - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) A block of statements that set parameters of the learner for this classifier; second argument to with.

LearnerToText - Class in edu.illinois.cs.cogcomp.lbjava.learn

This extremely simple class can be used to print a textual representation of a trained learner to STDOUT.

LearnerToText() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LearnerToText

LearningClassifierExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents expressions that specify classifiers that learn.

LearningClassifierExpression(ClassifierExpression, ClassifierExpression, InstanceCreationExpression, Expression, InstanceCreationExpression, Name, Block, Constant, InstanceCreationExpression, Expression, Constant, LinkedList<ParameterSet>, FoldParser.SplitPolicy, InstanceCreationExpression, Constant, Constant, Constant, Constant, Constant, Constant, Integer, Integer, Integer, StringBuffer, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Full constructor.

LearningClassifierExpression(LinkedList<LearningClassifierExpression.Clause>, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Parser's unsupervised learning constructor.

LearningClassifierExpression(ClassifierExpression, LinkedList<LearningClassifierExpression.Clause>, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Parser's supervised learning constructor.

LearningClassifierExpression.Clause - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents a clause in a LearningClassifierExpression.

learningRate - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

The rate at which weights are updated; default LinearThresholdUnit.defaultLearningRate.

learningRate - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit.Parameters

The rate at which weights are updated; default LinearThresholdUnit.defaultLearningRate.

learningRate - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

The rate at which weights are updated; default StochasticGradientDescent.defaultLearningRate.

learningRate - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent.Parameters

The rate at which weights are updated; default StochasticGradientDescent.defaultLearningRate.

learningRateA - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

learningRateP - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad.Parameters

learningStatus - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

The revision status of the LCE's learning node.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

One feature argument.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

One feature argument.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderBinaryConstraint

The constraint on the left of the operator.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityTwoValues

The value on the left of the equality.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithValue

The variable on the left of the equality.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithVariable

The variable on the left of the equality.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalBinaryConstraint

The constraint on the left of the operator.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Assignment

(¬ø) The left hand side of the assignment.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryConstraintExpression

(¬ø) The left hand side of the binary expression.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryExpression

(¬ø) The left hand side of the binary expression.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Conjunction

(¬ø) The left hand side of the conjunction.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

(¬ø) The expression on the left hand side of the operator.

left - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InstanceofExpression

(¬ø) The expression on the left hand side of instanceof.

LEFT_SHIFT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

LEFT_SHIFT_ASSIGN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

leftConstant - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.EqualityArgumentReplacer

This flag is set if the left hand side of the equality is not quantified.

leftIsDiscreteLearner - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

Filled in by SemanticAnalysis, this flag is set if left represents the invocation of a discrete learner.

leftIsQuantified - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

Filled in by SemanticAnalysis, this flag is set if left contains any quantified variables.

length() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Name

Returns the length of the name array.

length() - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Returns the length of ByteString.value.

LESS_THAN - Static variable in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Represents the constraint type "less than or equal to".

LESS_THAN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

LESS_THAN_OR_EQUAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

lexFilePath - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Caches the location of this learner's offline lexicon.

lexicon - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Stores the feature Lexicon.

Lexicon - Class in edu.illinois.cs.cogcomp.lbjava.learn

A Lexicon contains a mapping from Features to integers.

Lexicon() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Creates an empty lexicon.

Lexicon(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Creates an empty lexicon with the given encoding.

lexicon - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

The map of features to integer keys.

Lexicon.CountPolicy - Class in edu.illinois.cs.cogcomp.lbjava.learn

Immutable type representing the feature counting policy of a lexicon.

Lexicon.PruningPolicy - Class in edu.illinois.cs.cogcomp.lbjava.learn

Represents the feature counting policy of a lexicon.

lexiconChildren - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Stores features that might appear repeatedly as children of other features, but which are not themselves given indexes in the lexicon.

lexiconInv - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

The inverted map of integer keys to their features.

lexiconSize - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

The number of features extracted during pre-extraction.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, Lexicon, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Reads the representation of a feature with this object's run-time type as stored by a lexicon, overwriting the data in this object.

lexRead(ExceptionlessInputStream, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Reads the representation of a byte string as stored by a lexicon, overwriting the data in this object.

lexReadByteString(ExceptionlessInputStream, ByteString) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Reads and returns a byte string as written by a lexicon.

lexReadFeature(ExceptionlessInputStream, Lexicon, Class, String, String, String, ByteString) - Static method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Reads the representation of a feature of any type as stored by a lexicon, omitting redundant information.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, Lexicon, String, String, String, String, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Writes a binary representation of the feature intended for use by a lexicon, omitting redundant information when possible.

lexWrite(ExceptionlessOutputStream, ByteString) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Writes a binary representation of this byte string intended for use by a lexicon, omitting redundant information when possible.

line - Variable in class edu.illinois.cs.cogcomp.lbjava.frontend.TokenValue

The line on which the token is found in the source file.

line - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNode

The line on which the source code represented by this node is found.

LinearThresholdUnit - Class in edu.illinois.cs.cogcomp.lbjava.learn

A LinearThresholdUnit is a Learner for binary classification in which a score is computed as a linear function a weight vector and the input example, and the decision is made by comparing the score to some threshold quantity.

LinearThresholdUnit() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Default constructor.

LinearThresholdUnit(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Initializing constructor.

LinearThresholdUnit(double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Sets the learning rate and threshold to the specified values, while the name of the classifier gets the empty string.

LinearThresholdUnit(double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Use this constructor to fit a thick separator, where both the positive and negative sides of the hyperplane will be given the specified thickness, while the name of the classifier gets the empty string.

LinearThresholdUnit(double, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Use this constructor to fit a thick separator, where the positive and negative sides of the hyperplane will be given the specified separate thicknesses, while the name of the classifier gets the empty string.

LinearThresholdUnit(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Initializing constructor.

LinearThresholdUnit(String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Default constructor.

LinearThresholdUnit(String, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Initializing constructor.

LinearThresholdUnit(String, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Initializing constructor.

LinearThresholdUnit(String, double, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Initializing constructor.

LinearThresholdUnit(String, double, double, double, double, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Initializing constructor.

LinearThresholdUnit(LinearThresholdUnit.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Initializing constructor.

LinearThresholdUnit(String, LinearThresholdUnit.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Initializing constructor.

LinearThresholdUnit.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of LinearThresholdUnit's configurable parameters.

LineByLine - Class in edu.illinois.cs.cogcomp.lbjava.parse

This abstract Parser does not define the next() method, but it does define a constructor that opens the specified file and a readLine() method that fetches the next line of text from that file, taking care of exception handling.

LineByLine() - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.LineByLine

Leaves the member variables uninitialized.

LineByLine(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.LineByLine

Creates the parser.

LinkedChild - Class in edu.illinois.cs.cogcomp.lbjava.parse

A LinkedChild is the child of a LinkedVector.

LinkedChild() - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.LinkedChild

Does nothing.

LinkedChild(LinkedChild) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.LinkedChild

Useful when the information that this child represents is parsed forwards.

LinkedChild(int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.LinkedChild

Constructor that sets the byte offsets of this child.

LinkedChild(LinkedChild, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.LinkedChild

Useful when the information that this child represents is parsed forwards.

LinkedVector - Class in edu.illinois.cs.cogcomp.lbjava.parse

A LinkedVector is used to store a vector of LinkedChildren which all maintain links between each other and the parent LinkedVector.

LinkedVector() - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

Initializes the vector.

LinkedVector(LinkedChild) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

Constructor for when only a single child from anywhere in this vector is available.

LinkedVector(LinkedVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

Useful when the information that this child represents is parsed forwards.

LinkedVector(int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

Constructor that sets the character offsets of this vector.

LinkedVector(LinkedChild, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

Constructor for when only a single child from anywhere in this vector is available.

LinkedVector(LinkedVector, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

Useful when the information that this child represents is parsed forwards.

List - Class in edu.illinois.cs.cogcomp.lbjava.IR

Currently, this is just a wrapper class for LinkedList.

List(int, int, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.List

Full constructor.

list - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.List

(¬ø) The list being wrapped.

List.NodeListIterator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Used to iterate though the children of a list of AST nodes.

listIterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchList

Returns an iterator used specifically to access the elements of this list.

listIterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpressionList

Returns an iterator used specifically to access the elements of this list.

listIterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

Returns an iterator used specifically to access the elements of this list.

listIterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DeclarationList

Returns an iterator used specifically to access the elements of this list.

listIterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList

Returns an iterator used specifically to access the elements of this list.

listIterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportList

Returns an iterator used specifically to access the elements of this list.

listIterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NameList

Returns an iterator used specifically to access the elements of this list.

listIterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Returns a list iterator over ParameterSet.parameterList.

listIterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.StatementList

Returns an iterator used specifically to access the elements of this list.

listIterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroupList

Returns an iterator used specifically to access the elements of this list.

listIterator() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabelList

Returns an iterator used specifically to access the elements of this list.

LITERAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

ljust(String, int) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Returns a space-padded string of at least the specified width such that the argument string is left-justified within the returned string.

loadFromClasspath(Class, String) - Static method in class edu.illinois.cs.cogcomp.lbjava.io.IOUtilities

localContainsKey(ClassifierName) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Determines whether the specified name has been used as a key in this table.

localContainsKey(Name) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Determines whether the specified name has been used as a key in this table.

localContainsKey(String) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Determines whether the specified name has been used as a key in this table.

Log - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply turns each score s in the ScoreSet returned by the specified Normalizer into log(s).

Log() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Log

This constructor provided for use by the LBJava compiler only.

Log(Normalizer) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Log

Initializing constructor.

logCount - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Count

The natural logartihm of NaiveBayes.Count.count is sometimes stored here.

logFactorial(double) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.StudentT

log to base e of the factorial of n.

logGamma(double) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.StudentT

log to base e of the Gamma function, Lanczos approximation (6 terms).

LOGICAL_CONJUNCTION - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

LOGICAL_DISJUNCTION - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

LONG - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

LONG - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Value of the type variable.

lookup(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Looks up a feature's index by calling lookup(f, false).

lookup(Feature, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Looks up a feature's index by calling lookup(f, training, -1).

lookup(Feature, boolean, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Looks up the given feature in the lexicon, possibly counting it and/or expanding the lexicon to accomodate it.

lookupChild(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Unlike the overridden method in Lexicon, this method simply checks Lexicon.lexicon for the feature and will throw an exception if it can't be found.

lookupChild(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Used to lookup the children of conjunctive and referring features while writing the lexicon, this method checks Lexicon.lexiconChildren if the feature isn't present in Lexicon.lexicon and Lexicon.lexiconInv, and will throw an exception if it still can't be found.

lookupKey(int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Does a reverse lexicon lookup and returns the Feature associated with the given integer key, and null if no such feature exists.

lossFlag - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

To use a different score function based on the loss, set this flag.

lossFunctionA - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

lossFunctionP - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad.Parameters

lowerBound - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.AtLeastQuantifierExpression

(¬ø) This expression evaluates to an integer representing the minimum number of objects that must satisfy the child constraint expression in order for this quantified constraint expression to be satisfied.

lowerBound - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

A lower bound for an index relating to the pivot fold.

lowerBoundIsQuantified - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.AtLeastQuantifierExpression

Filled in by SemanticAnalysis, this flag is set if lowerBound contains any quantified variables.

LPAREN - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

LSHIFT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

LSHIFTEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

LT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

LTEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

M

m - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.AtLeastQuantifier

The number of objects for which the constraint must hold.

m - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.AtMostQuantifier

The maximum number of objects for which the constraint must hold.

m - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

The number of child constraints that must be true.

main(String[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

The entry point of this program.

main(String[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.frontend.GenerateParserAndSymbols

main(String[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.LearnerToText

main(String[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Main - Class in edu.illinois.cs.cogcomp.lbjava

LBJava's command line interface.

Main() - Constructor for class edu.illinois.cs.cogcomp.lbjava.Main

main(String[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.Main

The main compiler driver.

main(String[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

makeConstraint(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ParameterizedConstraint

This method builds a first order constraint based on the given input object.

makeReal() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Returns a RealArrayFeature whose value field is set to the strength of the current feature, and whose DiscretePrimitiveFeature.identifier field contains all the information necessary to distinguish this feature from other features.

makeReal() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Returns a RealArrayFeature whose value field is set to the strength of the current feature, and whose DiscretePrimitiveStringFeature.identifier field contains all the information necessary to distinguish this feature from other features.

makeReal() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Returns a RealConjunctiveFeature with exactly the same children as this feature.

makeReal() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Returns a RealPrimitiveFeature whose value field is set to the strength of the current feature, and whose DiscretePrimitiveFeature.identifier field contains all the information necessary to distinguish this feature from other features.

makeReal() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Returns a RealPrimitiveFeature whose value field is set to the strength of the current feature, and whose DiscretePrimitiveStringFeature.identifier field contains all the information necessary to distinguish this feature from other features.

makeReal() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Returns a RealPrimitiveFeature whose value field is set to the strength of the current feature, and whose DiscreteReferringFeature.identifier field contains all the information necessary to distinguish this feature from other features.

makeReal() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Returns a RealPrimitiveFeature whose value field is set to the strength of the current feature, and whose DiscreteReferringStringFeature.identifier field contains all the information necessary to distinguish this feature from other features.

makeReal() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Returns a RealFeature whose value is the strength of the current feature, and whose identifier field contains all the information necessary to distinguish this feature from other features.

makeReal() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Converts all of the features in the FeatureVector.features list to RealFeatures with appropriate strengths.

makeReal() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealFeature

Simply returns this object.

makeTypeReadable(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

The value returned by the Class.getName() method is not recognizable as a type by javac if the given class is an array; this method produces a representation that is recognizable by javac.

manual - Static variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser.SplitPolicy

Represents the split policy in which the user manually inserts fold separation objects.

mapCache - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

This value is used in place of the field access which appears as an argument to cachedin to indicate that in fact, cached was used instead.

mark(int) - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexInputStream

Marks the current position in this input stream.

mark(int) - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexStringInputStream

Marks the current position in this input stream.

markSupported() - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexInputStream

Tests if this input stream supports the mark and reset methods.

markSupported() - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexStringInputStream

Tests if this input stream supports the mark and reset methods.

MAXIMIZE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

maximize - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Remembers whether the objective function should be maximized or minimzed.

message - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.AssertStatement

(ø) Represents the error message in the assertion error, if any.

messageIndent - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Spacing for making status messages prettier.

MethodInvocation - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents a method call.

MethodInvocation(Name) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Initializing constructor.

MethodInvocation(Name, ExpressionList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Initializing constructor.

MethodInvocation(Expression, TokenValue) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Parser's constructor.

MethodInvocation(Expression, TokenValue, ExpressionList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Parser's constructor.

MethodInvocation(Expression, Name, ExpressionList, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Full constructor.

MINIMIZE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

MINUS - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

MINUS - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

MINUS_ASSIGN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

MINUSEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

MINUSMINUS - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

MIXED - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

MIXED - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Value of the type variable.

MIXED_ARRAY - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Value of the type variable.

MIXED_GENERATOR - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Value of the type variable.

MOD - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

MOD - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

MOD_ASSIGN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

MODEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

moreGeneralThan(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Compares topology to determine if this constraint is more general than the given constraint; note: this method is not required to be correct when it answers false.

moreGeneralThan(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Compares topology to determine if this constraint is more general than the given constraint; note: this method is not required to be correct when it answers false.

moreGeneralThan(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Compares topology to determine if this constraint is more general than the given constraint; note: this method is not required to be correct when it answers false.

moreGeneralThan(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Compares topology to determine if this constraint is more general than the given constraint; note: this method is not required to be correct when it answers false.

moreGeneralThan(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Compares topology to determine if this constraint is more general than the given constraint; note: this method is not required to be correct when it answers false.

moreGeneralThan(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Compares topology to determine if this constraint is more general than the given constraint; note: this method is not required to be correct when it answers false.

moreGeneralThan(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Compares topology to determine if this constraint is more general than the given constraint; note: this method is not required to be correct when it answers false.

moreGeneralThan(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Compares topology to determine if this constraint is more general than the given constraint; note: this method is not required to be correct when it answers false.

moreGeneralThan(PropositionalConstraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Compares topology to determine if this constraint is more general than the given constraint; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Compares topology to determine if this constraint is more specific than the given implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDoubleImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Compares topology to determine if this constraint is more specific than the given double implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Compares topology to determine if this constraint is more specific than the given conjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Compares topology to determine if this constraint is more specific than the given disjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalAtLeast) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Compares topology to determine if this constraint is more specific than the given at-least; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalNegation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Compares topology to determine if this constraint is more specific than the given negation; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Compares topology to determine if this constraint is more specific than the given variable; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConstant) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Compares topology to determine if this constraint is more specific than the given constant; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Compares topology to determine if this constraint is more specific than the given implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDoubleImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Compares topology to determine if this constraint is more specific than the given double implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Compares topology to determine if this constraint is more specific than the given conjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Compares topology to determine if this constraint is more specific than the given disjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalAtLeast) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Compares topology to determine if this constraint is more specific than the given at-least; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalNegation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Compares topology to determine if this constraint is more specific than the given negation; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Compares topology to determine if this constraint is more specific than the given variable; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConstant) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Compares topology to determine if this constraint is more specific than the given constant; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Compares topology to determine if this constraint is more specific than the given implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDoubleImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Compares topology to determine if this constraint is more specific than the given double implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Compares topology to determine if this constraint is more specific than the given conjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Compares topology to determine if this constraint is more specific than the given disjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalAtLeast) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Compares topology to determine if this constraint is more specific than the given at-least; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalNegation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Compares topology to determine if this constraint is more specific than the given negation; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Compares topology to determine if this constraint is more specific than the given variable; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConstant) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Compares topology to determine if this constraint is more specific than the given constant; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Compares topology to determine if this constraint is more specific than the given implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDoubleImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Compares topology to determine if this constraint is more specific than the given double implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Compares topology to determine if this constraint is more specific than the given conjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Compares topology to determine if this constraint is more specific than the given disjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalAtLeast) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Compares topology to determine if this constraint is more specific than the given at-least; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalNegation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Compares topology to determine if this constraint is more specific than the given negation; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Compares topology to determine if this constraint is more specific than the given variable; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConstant) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Compares topology to determine if this constraint is more specific than the given constant; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Compares topology to determine if this constraint is more specific than the given implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDoubleImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Compares topology to determine if this constraint is more specific than the given double implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Compares topology to determine if this constraint is more specific than the given conjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Compares topology to determine if this constraint is more specific than the given disjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalAtLeast) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Compares topology to determine if this constraint is more specific than the given at-least; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalNegation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Compares topology to determine if this constraint is more specific than the given negation; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Compares topology to determine if this constraint is more specific than the given variable; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConstant) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Compares topology to determine if this constraint is more specific than the given constant; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Compares topology to determine if this constraint is more specific than the given implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDoubleImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Compares topology to determine if this constraint is more specific than the given double implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Compares topology to determine if this constraint is more specific than the given conjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Compares topology to determine if this constraint is more specific than the given disjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalAtLeast) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Compares topology to determine if this constraint is more specific than the given at-least; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalNegation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Compares topology to determine if this constraint is more specific than the given negation; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Compares topology to determine if this constraint is more specific than the given variable; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConstant) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Compares topology to determine if this constraint is more specific than the given constant; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Compares topology to determine if this constraint is more specific than the given implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDoubleImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Compares topology to determine if this constraint is more specific than the given double implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Compares topology to determine if this constraint is more specific than the given conjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Compares topology to determine if this constraint is more specific than the given disjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalAtLeast) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Compares topology to determine if this constraint is more specific than the given at-least; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalNegation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Compares topology to determine if this constraint is more specific than the given negation; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Compares topology to determine if this constraint is more specific than the given variable; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConstant) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Compares topology to determine if this constraint is more specific than the given constant; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Compares topology to determine if this constraint is more specific than the given implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDoubleImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Compares topology to determine if this constraint is more specific than the given double implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Compares topology to determine if this constraint is more specific than the given conjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Compares topology to determine if this constraint is more specific than the given disjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalAtLeast) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Compares topology to determine if this constraint is more specific than the given at-least; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalNegation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Compares topology to determine if this constraint is more specific than the given negation; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Compares topology to determine if this constraint is more specific than the given variable; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConstant) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Compares topology to determine if this constraint is more specific than the given constant; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Compares topology to determine if this constraint is more specific than the given implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDoubleImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Compares topology to determine if this constraint is more specific than the given double implication; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Compares topology to determine if this constraint is more specific than the given conjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Compares topology to determine if this constraint is more specific than the given disjunction; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalAtLeast) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Compares topology to determine if this constraint is more specific than the given at-least; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalNegation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Compares topology to determine if this constraint is more specific than the given negation; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Compares topology to determine if this constraint is more specific than the given variable; note: this method is not required to be correct when it answers false.

moreSpecificThan(PropositionalConstant) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Compares topology to determine if this constraint is more specific than the given constant; note: this method is not required to be correct when it answers false.

MULTEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

MultiLabelLearner - Class in edu.illinois.cs.cogcomp.lbjava.learn

A simple implementation of a learner that learns from examples with multiple labels and is capable of predicting multiple labels on new examples.

MultiLabelLearner() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner

Instantiates this multi-label learner with the default learning algorithm: SparsePerceptron.

MultiLabelLearner(LinearThresholdUnit) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner

Instantiates this multi-label learner using the specified algorithm to learn each class separately as a binary classifier.

MultiLabelLearner(MultiLabelLearner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner

Initializing constructor.

MultiLabelLearner(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner

Instantiates this multi-label learner with the default learning algorithm: SparsePerceptron.

MultiLabelLearner(String, LinearThresholdUnit) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner

Instantiates this multi-label learner using the specified algorithm to learn each class separately as a binary classifier.

MultiLabelLearner(String, MultiLabelLearner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner

Initializing constructor.

MultiLabelLearner.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of MultiLabelLearner's configurable parameters.

multiply(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Returns a new feature object, the same as this one in all respects except the RealPrimitiveFeature.value field has been multiplied by the specified number.

multiply(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Returns a new feature object, the same as this one in all respects except the RealPrimitiveStringFeature.value field has been multiplied by the specified number.

multiply(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Returns a new feature object, the same as this one in all respects except the value has been multiplied by the specified number.

multiply(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealFeature

Returns a new feature object, the same as this one in all respects except the value has been multiplied by the specified number.

multiply(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Returns a new feature object, the same as this one in all respects except the RealPrimitiveFeature.value field has been multiplied by the specified number.

multiply(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Returns a new feature object, the same as this one in all respects except the RealPrimitiveStringFeature.value field has been multiplied by the specified number.

multiply(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Returns a new feature object, the same as this one in all respects except the RealReferrer.referent field has been multiplied by the specified number.

multiply(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Returns a new feature object, the same as this one in all respects except the RealReferrer.referent field has been multiplied by the specified number.

MULTIPLY_ASSIGN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

MultiValueComparer - Class in edu.illinois.cs.cogcomp.lbjava.classify

This classifier applies another classifier to the example object and returns a Boolean feature (with value "true" or "false") indicating whether a given feature value appeared in the output of the classifier.

MultiValueComparer(Classifier, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.MultiValueComparer

Constructor.

MuxLearner - Class in edu.illinois.cs.cogcomp.lbjava.learn

A MuxLearner uses one of many Learners indexed by the first feature in an example to produce a classification.

MuxLearner() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

For the LBJava compiler; not for use by the LBJava user.

MuxLearner(Learner) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Instantiates this multiplexed learner using the specified base learning algorithm.

MuxLearner(Learner, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Instantiates this multiplexed learner using the specified base learning algorithm.

MuxLearner(MuxLearner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Initializing constructor.

MuxLearner(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

For the LBJava compiler; not for use by the LBJava user.

MuxLearner(String, Learner) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Instantiates this multiplexed learner using the specified base learning algorithm.

MuxLearner(String, Learner, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Instantiates this multiplexed learner using the specified base learning algorithm.

MuxLearner(String, MuxLearner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Initializing constructor.

MuxLearner.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of MuxLearner's configurable parameters.

myClass - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Type

Java's Class object defining the class that this Type represents.

N

NaiveBayes - Class in edu.illinois.cs.cogcomp.lbjava.learn

Naive Bayes is a multi-class learner that uses prediction value counts and feature counts given a particular prediction value to select the most likely prediction value.

NaiveBayes() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Default constructor.

NaiveBayes(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Initializes the smoothing constant.

NaiveBayes(NaiveBayes.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Initializing constructor.

NaiveBayes(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Initializes the name of the classifier.

NaiveBayes(String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Initializes the name and smoothing constant.

NaiveBayes(String, NaiveBayes.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Initializing constructor.

NaiveBayes.Count - Class in edu.illinois.cs.cogcomp.lbjava.learn

A Count object stores two doubles, one which holds a accumulated count value and the other intended to hold the natural logarithm of the count.

NaiveBayes.NaiveBayesVector - Class in edu.illinois.cs.cogcomp.lbjava.learn

Keeps track of all the counts associated with a given label.

NaiveBayes.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of NaiveBayes's configurable parameters.

NaiveBayesVector() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Simply instantiates NaiveBayes.NaiveBayesVector.counts.

NaiveBayesVector(NaiveBayes.Count[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Simply initializes NaiveBayes.NaiveBayesVector.counts.

NaiveBayesVector(OVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Simply initializes NaiveBayes.NaiveBayesVector.counts.

name - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

The name of the classifier usually becomes the identifier of produced features.

name - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpression

Expression describing what is being declared.

name - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Declaration

(¬ø) Identifies what is being declared.

name - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.FieldAccess

(¬ø) The name of the field to be accessed.

name - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

(¬ø) The name of the method to be invoked.

Name - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents a scalar variable.

Name(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Name

Takes a fully specified name (eg java.lang.String) as input.

Name(String, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Name

Takes a fully specified name (eg java.lang.String) as input.

Name(String[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Name

Should only be called by the clone() method.

Name(String[], int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Name

Should only be called by the clone() method.

Name(TokenValue) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Name

Parser's constructor.

Name(Name, TokenValue) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Name

Parser's constructor.

name - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Name

(¬ø) These strings appeared with dots between them to form the name in the source.

name - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

(ø) Represents the name of the feature being sensed (only used in generators).

NameList - Class in edu.illinois.cs.cogcomp.lbjava.IR

Currently, this is just a wrapper class for LinkedList.

NameList() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.NameList

Default constructor.

NameList(Name) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.NameList

Initializing constructor.

NameList.NameListIterator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Used to iterate though the children of a list of AST nodes.

NameListIterator() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.NameList.NameListIterator

names - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

(¬ø) The names of variables declared in this statement.

nameTable - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.SymbolNames

NATIVE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

negate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

The negation of an at-least(m) is the at-least(n-m+1) of the negated children.

negate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Uses DeMorgan's law to compute the negation of this constraint by distributing that negation to each child.

negate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Produces a new propositional constraint equivalent to this constraint and that contains no negated constraints other than variables.

negate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Produces a new propositional constraint equivalent to this constraint and that contains no negated constraints other than variables.

negate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Uses DeMorgan's law to compute the negation of this constraint by distributing that negation to each child.

negate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Produces a new propositional constraint equivalent to this constraint and that contains no negated constraints other than variables.

negate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Produces a new propositional constraint equivalent to this constraint and that contains no negated constraints other than variables.

negate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Produces a new propositional constraint equivalent to this constraint and that contains no negated constraints other than variables.

negate() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Produces a new propositional constraint equivalent to this constraint and that contains no negated constraints other than variables.

NegatedConstraintExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents the negation of a constraint expression.

NegatedConstraintExpression(int, int, ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.NegatedConstraintExpression

Full constructor.

NegatedConstraintExpression(TokenValue, ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.NegatedConstraintExpression

Parser's constructor.

negativeThickness - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

The thickness of the hyperplane on the negative side; default equal to LinearThresholdUnit.positiveThickness.

negativeThickness - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit.Parameters

The thickness of the hyperplane on the negative side; default 0.

network - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

A map from feature values to learners.

network - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

One NaiveBayes.NaiveBayesVector for each observed prediction value.

network - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

A map from labels to the weight vector corresponding to that label.

network - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

A collection of the linear threshold units used to learn each label, indexed by the label.

NEW - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

NEW - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

newCode - Variable in class edu.illinois.cs.cogcomp.lbjava.Train

Set to true iff there existed a LearningClassifierExpression for which new code was generated.

newLabelLexicon - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Created during SupportVectorMachine.doneLearning() in case the training examples observed by SupportVectorMachine.learn(int[],double[],int[],double[]) are only a subset of a larger, pre-extracted set.

next() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNodeIterator

Returns the next child AST node.

next() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List.NodeListIterator

Returns the next AST node in the list.

next() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

Returns either an Object[] or a FoldSeparator deserialized out of the given file.

next() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayParser

Returns the next example in the array and increments the ArrayParser.index pointer.

next - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.ChildrenFromVectors

The next child to be returned.

next() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.ChildrenFromVectors

Returns the next LinkedChild parsed.

next() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Retrieves the next example object.

next - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedChild

A link to the next child in the parent vector.

next() - Method in interface edu.illinois.cs.cogcomp.lbjava.parse.Parser

Use this method to retrieve the next object parsed from the raw input data.

next_token() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.Yylex

nextChoice(int[], int) - Static method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Given a particular choice of k of the first n non-negative integers, this method computes the next logical choice of k integers, modifying the input array to contain that choice.

nextID - Static variable in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Keeps the next ID number for objects of this class.

nextIndex() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List.NodeListIterator

Returns the index of the node that would be returned by a subsequent call to next().

nextItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchList.CatchListIterator

Returns the next AST node in the list.

nextItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpressionList.ClassifierExpressionListIterator

Returns the next AST node in the list.

nextItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList.ConstantListIterator

Returns the next AST node in the list.

nextItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DeclarationList.DeclarationListIterator

Returns the next AST node in the list.

nextItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList.ExpressionListIterator

Returns the next AST node in the list.

nextItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportList.ImportListIterator

Returns the next AST node in the list.

nextItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NameList.NameListIterator

Returns the next AST node in the list.

nextItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.StatementList.StatementListIterator

Returns the next AST node in the list.

nextItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroupList.SwitchGroupListIterator

Returns the next AST node in the list.

nextItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabelList.SwitchLabelListIterator

Returns the next AST node in the list.

noChanges - Static variable in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Set to true iff no code has changed since the compiler was last run.

nodeID - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNode

Stores the ID of this node as provided by nextID.

NodeListIterator() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.List.NodeListIterator

Initializes I.

nonDefaultString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost.Parameters

Creates a string representation of these parameters in which only those parameters that differ from their default values are mentioned.

nonDefaultString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA.Parameters

Creates a string representation of these parameters in which only those parameters that differ from their default values are mentioned.

nonDefaultString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner.Parameters

Creates a string representation of these parameters in which only those parameters that differ from their default values are mentioned.

nonDefaultString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit.Parameters

Creates a string representation of these parameters in which only those parameters that differ from their default values are mentioned.

nonDefaultString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner.Parameters

Creates a string representation of these parameters in which only those parameters that differ from their default values are mentioned.

nonDefaultString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Parameters

Creates a string representation of these parameters in which only those parameters that differ from their default values are mentioned.

nonDefaultString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted.Parameters

Creates a string representation of these parameters in which only those parameters that differ from their default values are mentioned.

nonDefaultString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner.Parameters

Creates a string representation of these parameters in which only those parameters that differ from their default values are mentioned.

nonDefaultString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow.Parameters

Creates a string representation of these parameters in which only those parameters that differ from their default values are mentioned.

nonDefaultString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent.Parameters

Creates a string representation of these parameters in which only those parameters that differ from their default values are mentioned.

nonDefaultString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine.Parameters

Creates a string representation of these parameters in which only those parameters that differ from their default values are mentioned.

nonDefaultString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper.Parameters

Creates a string representation of these parameters in which only those parameters that differ from their default values are mentioned.

none - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.CountPolicy

Represents no counting.

NONE - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

Represents no pruning.

nonTerminal(String, ASTNode) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

The default routine for printing a non-terminal AST node is to first print the name of the AST node's class with line and byte offset information, and then recursively print its children at indentation level one higher.

noQuotes() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Constant

Returns the contents of value removing unescaped double quotes.

normalize(ScoreSet) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.IdentityNormalizer

Simply returns the argument.

normalize(ScoreSet) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Log

Normalizes the given ScoreSet; its scores are modified in place before it is returned.

normalize(ScoreSet) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Normalizer

Normalizes the given ScoreSet; its scores are modified in place before it is returned.

normalize(ScoreSet) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Sigmoid

Normalizes the given ScoreSet; its scores are modified in place before it is returned.

normalize(ScoreSet) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Softmax

Normalizes the given ScoreSet; its scores are modified in place before it is returned.

NORMALIZEDBY - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

normalizer - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.NormalizerDeclaration

(¬ø) Constructs the normalizer to use.

Normalizer - Class in edu.illinois.cs.cogcomp.lbjava.learn

A normalizer is a function of a ScoreSet producing normalized scores.

Normalizer() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Normalizer

NORMALIZER_DECLARATION - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.Clause

Value of the type variable.

NormalizerDeclaration(int, int, Name, InstanceCreationExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.NormalizerDeclaration

Full constructor.

NormalizerDeclaration(TokenValue, Name, InstanceCreationExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.NormalizerDeclaration

Parser's constructor.

normalizerDeclarations - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

(¬ø) Declarations describing how the scores produced by various learning classifiers should be normalized.

NormalizerType - Class in edu.illinois.cs.cogcomp.lbjava.IR

A normalizer type is simply a place holder indicating that the name it is associated with in the symbol table is a normalizer function.

NormalizerType() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.NormalizerType

Default constructor.

NOT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

NOT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

NOT_EQUAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

NOTEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

nullLabels - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

The set of "null" labels whose statistics are not included in overall precision, recall, F1, or accuracy.

numClasses - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

The number of unique class labels seen during training.

numExamples - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

The total number of examples in the training data, or 0 if unknown.

numFeatures - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

The total number of distinct features in the training data, or 0 if unknown.

numFeatures - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

The number of unique features seen during training.

O

object - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.FieldAccess

(¬ø) The expression describing the object to be accessed.

objectiveCoefficients - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Represents the coefficients of all inference variables in the objective function.

objectiveValue() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

When the problem has been solved, use this method to retrieve the value of the objective function at the solution.

OF - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

onlyCodeGeneration - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

This flag is set true iff the changes to the learner's LBJava specification require its Java translation to be regenerated and nothing more.

open(CodeGenerator) - Static method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Create a PrintStream that writes to a Java file corresponding to the specified CodeGenerator.

open(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Create a PrintStream that writes to the specified file.

operation - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Assignment

(¬ø) The assignment operation.

operation - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryConstraintExpression

(¬ø) The binary operation.

operation - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryExpression

(¬ø) The binary operation.

operation - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

(¬ø) Represents either an equality or an inequality comparison.

operation - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.IncrementExpression

(¬ø) Representation of the increment operator.

operation - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

The index of the operation represented by this Operator.

operation - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.UnaryExpression

(¬ø) Representation of the unary operator.

Operator - Class in edu.illinois.cs.cogcomp.lbjava.IR

LBJava supports every Java operator.

Operator(int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Default constructor.

Operator(int, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Full constructor.

operatorPrecedence(int) - Static method in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Produces the precedence of an operator given its index.

operatorSymbol(int) - Static method in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Produces the name of an operator given its index.

OR - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

OR - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

OR_ASSIGN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

OREQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

OROR - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

output - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

The type of the classifier's output.

P

PACKAGE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

packageDeclaration - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.AST

(ø) An optional declaration of the package that generated classes should be a part of.

PackageDeclaration - Class in edu.illinois.cs.cogcomp.lbjava.IR

Representation of an package declaration.

PackageDeclaration(Name, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.PackageDeclaration

Full constructor.

pairwiseMultiply(int[], double[], double, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

The strength of each feature in the argument vector is multiplied by the corresponding weight in this weight vector and the result is returned as an array of arrays.

parameterized - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifiedConstraintInvocation

The parameterized constraint that has been invoked.

ParameterizedConstraint - Class in edu.illinois.cs.cogcomp.lbjava.infer

This class represents an LBJava constraint as it appears in a source file.

ParameterizedConstraint() - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ParameterizedConstraint

Default constructor.

ParameterizedConstraint(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ParameterizedConstraint

Initializes the name.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost.Parameters

Sets all the default values.

Parameters(Learner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(AdaBoost.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad.Parameters

Constructor for Parameters class use defaultLearningRate if not specified

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA.Parameters

Sets all the default values.

Parameters(SparsePerceptron.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(BinaryMIRA.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Learner.Parameters

Sets all the default values.

Parameters(Learner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Learner.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit.Parameters

Sets all the default values.

Parameters(Learner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(LinearThresholdUnit.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner.Parameters

Sets all the default values.

Parameters(SparseNetworkLearner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(MultiLabelLearner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner.Parameters

Sets all the default values.

Parameters(Learner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(MuxLearner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Parameters

Sets all the default values.

Parameters(Learner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(NaiveBayes.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive.Parameters

Sets all the default values.

Parameters(LinearThresholdUnit.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(PassiveAggressive.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.Parameters

Sets all the default values.

Parameters(SparsePerceptron.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(SparseAveragedPerceptron.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted.Parameters

Sets all the default values.

Parameters(LinearThresholdUnit.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(SparseConfidenceWeighted.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA.Parameters

Sets all the default values.

Parameters(Learner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(SparseMIRA.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner.Parameters

Sets all the default values.

Parameters(Learner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(SparseNetworkLearner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron.Parameters

Sets all the default values.

Parameters(LinearThresholdUnit.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(SparsePerceptron.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow.Parameters

Sets all the default values.

Parameters(LinearThresholdUnit.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(SparseWinnow.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent.Parameters

Sets all the default values.

Parameters(Learner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(StochasticGradientDescent.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine.Parameters

Sets all the default values.

Parameters(Learner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(SupportVectorMachine.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine.Parameters

Copy constructor.

Parameters() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper.Parameters

Sets all the default values.

Parameters(Learner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper.Parameters

Sets the parameters from the parent's parameters object, giving defaults to all parameters declared in this object.

Parameters(WekaWrapper.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper.Parameters

Copy constructor.

parametersClass - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

Train.TrainingThread.learner's Parameters class.

ParameterSet - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a set of possible parameters, used when doing parameter-tuning.

ParameterSet(ExpressionList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Initializing constructor.

ParameterSet(int, int, ExpressionList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Full constructor.

ParameterSet(Expression, Expression, Expression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Initializing constructor.

ParameterSet(int, int, Expression, Expression, Expression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Full constructor.

parameterSets - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

A list of the ParameterSet objects that appear in the argument list.

parent - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedChild

A link to this child's parent.

parenthesized - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpression

Indicates whether this expression was parenthesized in the source.

parenthesized - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintExpression

Indicates whether this expression was parenthesized in the source.

parenthesized - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Expression

Indicates whether this expression was parenthesized in the source.

parentObject - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

(ø) This expression evaluates to the object whose method will be called.

parser - Class in edu.illinois.cs.cogcomp.lbjava.frontend

CUP v0.11a beta 20060608 generated parser.

parser() - Constructor for class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Default constructor.

parser(Scanner) - Constructor for class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Constructor which sets the default scanner.

parser(Scanner, SymbolFactory) - Constructor for class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Constructor which sets the default scanner.

parser - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) Tells this learning classifier how to get its training data; argument to from.

parser - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

The parser from which training data for BatchTrainer.learner is received.

parser - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.ChildrenFromVectors

A parser that returns LinkedVectors.

parser - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

The parser whose examples are being filtered.

Parser - Interface in edu.illinois.cs.cogcomp.lbjava.parse

Any parser that extends this interface can be sent to a Learner for batch training.

parseType(Class) - Static method in class edu.illinois.cs.cogcomp.lbjava.IR.Type

This method takes a Java Class object and generates an LBJava Type that represents the same type.

parseType(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.IR.Type

This method takes a Java type encoding and generates an LBJava Type that represents the same type.

Pass - Class in edu.illinois.cs.cogcomp.lbjava

Abstract class from which all of LBJava's analysis and optimization passes are derived.

Pass() - Constructor for class edu.illinois.cs.cogcomp.lbjava.Pass

Default constructor.

Pass(ASTNode) - Constructor for class edu.illinois.cs.cogcomp.lbjava.Pass

Initializing constructor.

PassiveAggressive - Class in edu.illinois.cs.cogcomp.lbjava.learn

The Passive Aggressive learning algorithm implementation.

PassiveAggressive() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

The learning rate and threshold take default values, while the name of the classifier gets the empty string.

PassiveAggressive(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Sets the learning rate and threshold to the specified values, while the name of the classifier gets the empty string.

PassiveAggressive(double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Use this constructor to fit a thick separator, where both the positive and negative sides of the hyperplane will be given the specified thickness, while the name of the classifier gets the empty string.

PassiveAggressive(double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Use this constructor to fit a thick separator, where the positive and negative sides of the hyperplane will be given the specified separate thicknesses, while the name of the classifier gets the empty string.

PassiveAggressive(double, double, double, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Use this constructor to specify an alternative subclass of SparseWeightVector, while the name of the classifier gets the empty string.

PassiveAggressive(PassiveAggressive.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Initializing constructor.

PassiveAggressive(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Sets the learning rate to the specified value, and the threshold takes the default.

PassiveAggressive(String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Sets the learning rate and threshold to the specified values.

PassiveAggressive(String, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Use this constructor to fit a thick separator, where both the positive and negative sides of the hyperplane will be given the specified thickness.

PassiveAggressive(String, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Use this constructor to fit a thick separator, where the positive and negative sides of the hyperplane will be given the specified separate thicknesses.

PassiveAggressive(String, double, double, double, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Use this constructor to specify an alternative subclass of SparseWeightVector.

PassiveAggressive(String, PassiveAggressive.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Initializing constructor.

PassiveAggressive.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of PassiveAggressive's configurable parameters.

PERCENTAGE - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

Represents pruning with a percentage threshold.

perClass - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.CountPolicy

Represents per class counting.

perClassFeatureCounts - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Counts the number of occurrences of each feature on a class-by-class basis.

perClassToGlobalCounts() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Collapses per-class feature counts into global counts.

pivot - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

The examples from this fold are exclusively selected for or excluded from the set of examples returned by this parser.

PLUS - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

PLUS - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

PLUS_ASSIGN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

PLUSEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

PLUSPLUS - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

positiveThickness - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit.Parameters

The thickness of the hyperplane on the positive side; default 0.

positiveThickness - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

The thickness of the hyperplane on the positive side; default LinearThresholdUnit.defaultThickness.

POST_DECREMENT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

POST_INCREMENT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

PRE_DECREMENT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

PRE_INCREMENT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

prediction - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

The prediction that the classifier must produce for this variable to be true.

predictionHistogram - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

The histogram of predictions.

predictions - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Stores the set of predictions that this learner will choose from when classifying a new example.

PREEXTRACT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

PREEXTRACT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Value of the type variable

preExtract - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(¬ø) A Boolean or string value indicating how feature vectors are to be pre-extracted; argument to preExtract.

preExtract(String) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Performs labeled feature vector pre-extraction into the specified file (or memory), replacing BatchTrainer.parser with one that reads from that file (or memory).

preExtract(String, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Performs labeled feature vector pre-extraction into the specified file (or memory), replacing BatchTrainer.parser with one that reads from that file (or memory).

preExtract(String, Lexicon.CountPolicy) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Performs labeled feature vector pre-extraction into the specified file (or memory), replacing BatchTrainer.parser with one that reads from that file (or memory).

preExtract(String, boolean, Lexicon.CountPolicy) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Performs labeled feature vector pre-extraction into the specified file (or memory), replacing BatchTrainer.parser with one that reads from that file (or memory).

preExtract - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

Whether or not example vectors should be pre-extracted.

preExtractClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Counts the number of preExtract clauses for error detection.

preExtractZip - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

Whether or not pre-extracted example files should be compressed.

previous() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List.NodeListIterator

Returns the previous element in the list.

previous - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedChild

A link to the previous child in the parent vector.

previousIndex() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List.NodeListIterator

Returns the index of the node that would be returned by a subsequent call to previous().

previousItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchList.CatchListIterator

Returns the previous element in the list.

previousItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpressionList.ClassifierExpressionListIterator

Returns the previous element in the list.

previousItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList.ConstantListIterator

Returns the previous element in the list.

previousItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DeclarationList.DeclarationListIterator

Returns the previous element in the list.

previousItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList.ExpressionListIterator

Returns the previous element in the list.

previousItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportList.ImportListIterator

Returns the previous element in the list.

previousItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NameList.NameListIterator

Returns the previous element in the list.

previousItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.StatementList.StatementListIterator

Returns the previous element in the list.

previousItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroupList.SwitchGroupListIterator

Returns the previous element in the list.

previousItem() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabelList.SwitchLabelListIterator

Returns the previous element in the list.

previousPruneCountType - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) The contents of LearningClassifierExpression.pruneCountType on the previous run of the compiler, if any.

PrimitiveType - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a primitive type, as in a declaration.

PrimitiveType(int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Default constructor.

PrimitiveType(int, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Full constructor.

print() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Prints this table and all its children recursively to STDOUT.

print(String) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Prints this table and all its children recursively to STDOUT.

PrintAST - Class in edu.illinois.cs.cogcomp.lbjava

The PrintAST pass simply prints a text representation of the parsed AST to standard output.

PrintAST(AST) - Constructor for class edu.illinois.cs.cogcomp.lbjava.PrintAST

Instantiates a pass that runs on an entire AST.

printCountTable(boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Produces on STDOUT a table of feature counts including a line indicating the position of Lexicon.pruneCutoff.

printCountTable(boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Produces on STDOUT a table of feature counts including a line indicating the position of Lexicon.pruneCutoff.

printDependorGraph() - Static method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Prints the contents of SemanticAnalysis.dependorGraph to STDOUT in a readable form.

printErrorsAndWarnings() - Static method in class edu.illinois.cs.cogcomp.lbjava.Pass

Prints the errors and warnings to STDERR sorted by line.

printInvokedGraph() - Static method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Prints the contents of SemanticAnalysis.invokedGraph to STDOUT in a readable form.

printPerformace(PrintStream, int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestReal

Write to PrintStream, with statistical information

printPerformance(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Performance results are written to the given stream in the form of precision, recall, and F1 statistics.

printRevisionStatus() - Static method in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Prints the contents of RevisionAnalysis.revisionStatus to STDOUT.

printSymbols - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

This flag is set if symbol printing is enabled on the command line.

printTable(PrintStream, String[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Simply prints each element of the given array of strings to the given stream in its own line.

printTableFormat(PrintStream, double[][]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table and prints it to the given stream.

printTableFormat(PrintStream, Double[][]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table and prints it to the given stream.

printTableFormat(PrintStream, String[], String[], double[][]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table and prints it to the given stream.

printTableFormat(PrintStream, String[], String[], Double[][]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table and prints it to the given stream.

printTableFormat(PrintStream, String[], String[], double[][], int[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table and prints it to the given stream.

printTableFormat(PrintStream, String[], String[], Double[][], int[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table and prints it to the given stream.

printTableFormat(PrintStream, String[], String[], double[][], int[], int[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table and prints it to the given stream.

printTableFormat(PrintStream, String[], String[], Double[][], int[], int[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table and prints it to the given stream.

PrintUsage() - Static method in class edu.illinois.cs.cogcomp.lbjava.Main

Print a usage message.

priorCount - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

The prior count is the number of times either scaledAdd method has been called.

PRIVATE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

production_table() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Access to production table.

PROGRESSOUTPUT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

PROGRESSOUTPUT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Value of the type variable

progressOutput - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Determines how often to give the user status output during training.

progressOutput - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) Integer specifying how often (in examples) to give the user a progress update during training; argument to progressOutput.

progressOutput - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

The number of training examples in between status messages printed to STDOUT, or 0 to suppress these messages.

progressOutput - Variable in class edu.illinois.cs.cogcomp.lbjava.Train

Progress output will be printed every progressOutput examples.

progressOutputClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Counts the number of progressOutput clauses, for error detection.

promote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Scales the feature vector produced by the extractor by the learning rate and adds it to the weight vector.

promote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

If the LinearThresholdUnit is mistake driven, this method should be overridden and used to update the internal representation when a mistake is made on a positive example.

promote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Scales the feature vector produced by the extractor by the learning rate and adds it to the weight vector.

promote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Scales the feature vector produced by the extractor by the learning rate and adds it to the weight vector.

promote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

This method does nothing.

promote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Scales the feature vector produced by the extractor by the learning rate and adds it to the weight vector.

promote(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Promotion is simply w_i *= learningRatex_i.

PropositionalAtLeast - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents the constraint that at least m of the children constraints must be true.

PropositionalAtLeast(PropositionalConstraint[], int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Initializing constructor.

PropositionalBinaryConstraint - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents a propositional constraint involving a binary operator.

PropositionalBinaryConstraint(PropositionalConstraint, PropositionalConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalBinaryConstraint

Initializing constructor.

PropositionalConjunction - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents the conjunction of two propositional constraints.

PropositionalConjunction(PropositionalConstraint, PropositionalConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

If either of the arguments is itself a PropositionalConjunction, its contents are flattened into this PropositionalConjunction.

PropositionalConstant - Class in edu.illinois.cs.cogcomp.lbjava.infer

A propositional constant is either true or false.

PropositionalConstant(boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Initializing constructor.

PropositionalConstraint - Class in edu.illinois.cs.cogcomp.lbjava.infer

All classes for representing propositional constraints are derived from this base class.

PropositionalConstraint() - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

PropositionalDisjunction - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents the disjunction of two propositional constraints.

PropositionalDisjunction(PropositionalConstraint, PropositionalConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

If either of the arguments is itself a PropositionalDisjunction, its contents are flattened into this PropositionalDisjunction.

PropositionalDoubleImplication - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents a double implication between two propositional constraints.

PropositionalDoubleImplication(PropositionalConstraint, PropositionalConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Initializing constructor.

PropositionalImplication - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents an implication between two propositional constraints.

PropositionalImplication(PropositionalConstraint, PropositionalConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Initializing constructor.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.AtLeastQuantifier

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.AtMostQuantifier

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ExistentialQuantifier

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConjunction

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConstant

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConstraint

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDisjunction

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDoubleImplication

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityTwoValues

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithValue

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithVariable

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderImplication

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNegation

Transforms this first order constraint into a propositional constraint.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifiedConstraintInvocation

If this method is called without first calling setQuantificationVariables(Vector), the constant representing false will be returned.

propositionalize() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.UniversalQuantifier

Transforms this first order constraint into a propositional constraint.

PropositionalNAryConstraint - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents a propositional constraint with an arbitrary number of arguments, usually assumed to be greater than or equal to 2.

PropositionalNAryConstraint() - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNAryConstraint

Default constructor.

PropositionalNegation - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents the negation operator applied to a propositional constraint.

PropositionalNegation(PropositionalConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Initializing constructor.

PropositionalVariable - Class in edu.illinois.cs.cogcomp.lbjava.infer

Every propositional variable is Boolean and represents one possible prediction from a classifier application.

PropositionalVariable(Learner, Object, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Initializing constructor; the value member variable is set to false .

PROTECTED - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

PRUNE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

PRUNE - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Value of the type variable

prune(Lexicon.PruningPolicy) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Rearranges the order in which features appear in the lexicon based on the compiled feature counts in Lexicon.featureCounts or Lexicon.perClassFeatureCounts so that pruned features are at the end of the feature space.

pruneCountType - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Whether to use "global" or "perClass" feature pruning.

pruneCountType - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) Whether to use "global" or "perClass" feature pruning.

pruneCutoff - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Features at this index in Lexicon.lexiconInv or higher have been pruned.

pruneDataset(String, Lexicon.PruningPolicy, Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Prunes the data returned by BatchTrainer.parser according to the given policy, under the assumption that feature counts have already been compiled in the given learner's lexicon.

pruneDataset(String, boolean, Lexicon.PruningPolicy, Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Prunes the data returned by BatchTrainer.parser according to the given policy, under the assumption that feature counts have already been compiled in the given learner's lexicon.

pruneStatus - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

The revision status of the LCE's prune node.

pruneThreshold - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

The feature pruning threshold.

pruneThreshold - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) The feature pruning threshold.

pruneThresholdType - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Whether to use "count" or "percent" counting for feature pruning.

pruneThresholdType - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) Whether to use "count" or "percent" counting for feature pruning.

PruningPolicy() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

Creates a new pruning policy in which no features will be pruned.

PruningPolicy(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

Creates a new "Percentage" policy with the given percentage.

PruningPolicy(int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

Creates a new "Absolute" policy with the given threshold.

PUBLIC - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

put(String, double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ScoreSet

Sets the score for a particular classification value.

put(Inference) - Static method in class edu.illinois.cs.cogcomp.lbjava.infer.InferenceManager

Adds the given Inference object to the cache, indexed its fully qualified name.

put(String, Inference) - Static method in class edu.illinois.cs.cogcomp.lbjava.infer.InferenceManager

Adds the given Inference object to the cache, indexed by an arbitrary name (NB: Don't use unless you know what you're doing).

put(Argument) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Adds a new entry to the table.

put(ClassifierName, Type) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Adds a new entry to the table.

put(Name, Type) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Adds a new entry to the table.

put(String, Type) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Adds a new entry to the table.

Q

quantificationVariable - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.Quantifier

The name of the quantification variable.

quantificationVariables - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ArgumentReplacer

The settings of quantification variables in context at the equality in question.

QuantifiedConstraintExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

A quantified constraint expression is a compact way to specify a constraint as a function of every object in a given collection.

QuantifiedConstraintExpression(int, int, Argument, Expression, ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.QuantifiedConstraintExpression

Full constructor.

QuantifiedConstraintInvocation - Class in edu.illinois.cs.cogcomp.lbjava.infer

Represents the invocation of a parameterized constraint nested inside at least one quantification expression, where the parameter is a function of the quantification variables.

QuantifiedConstraintInvocation(ParameterizedConstraint, InvocationArgumentReplacer) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.QuantifiedConstraintInvocation

Initializing constructor.

Quantifier - Class in edu.illinois.cs.cogcomp.lbjava.infer

A quantifier is a first order constraint parameterized by an object taken from a Java Collection of objects.

Quantifier(String, Collection, FirstOrderConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.Quantifier

Initializing constructor.

Quantifier(String, Collection, FirstOrderConstraint, QuantifierArgumentReplacer) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.Quantifier

This constructor specifies a variable setter for when this quantifier is itself quantified.

QuantifierArgumentReplacer - Class in edu.illinois.cs.cogcomp.lbjava.infer

Anonymous inner classes extending this class are instantiated by the code generated by the LBJava compiler when creating FirstOrderConstraint representations.

QuantifierArgumentReplacer(Object[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.QuantifierArgumentReplacer

Initializing constructor.

QuantifierArgumentReplacer(Object[], boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.QuantifierArgumentReplacer

Use this constructor to indicate which of the two arguments of the equality is in fact not quantified.

quantifierArgumentType - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Type

Set true by SemanticAnalysis iff this type will be used to represent the argument of a QuantifiedConstraintExpression.

QUESTION - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

R

random - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

The random number generator for this instance.

random - Static variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser.SplitPolicy

Represents the random split policy.

RandomWeightVector - Class in edu.illinois.cs.cogcomp.lbjava.learn

This weight vector operates similarly to its parent in the class hierarchy, but it halucinates (and sets) random values for weights corresponding to features it has never been asked about before.

RandomWeightVector() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

Sets a default standard deviation.

RandomWeightVector(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

Sets the specified standard deviation.

RARROW - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

RBRACE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

RBRACEBRACE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

RBRACK - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Reads the representation of a feature with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Reads the representation of a feature with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Reads the binary representation of a feature vector from the specified stream, overwriting the contents of this vector.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Reads the representation of a feature with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Reads the representation of a feaeture with this object's run-time type from the given stream, overwriting the data in this object.

read() - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexInputStream

Reads the next byte of data from the input stream.

read(byte[]) - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexInputStream

This method has the same effect as read(b, 0, b.length).

read(byte[], int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexInputStream

Reads up to len bytes of data from another input stream into an array of bytes.

read() - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexStringInputStream

Reads the next char of data from the input stream.

read(char[]) - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexStringInputStream

This method has the same effect as read(b, 0, b.length).

read(char[], int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexStringInputStream

Reads up to len chars of data from another String into an array of chars.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

Reads the representation of a weight vector with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Reads a binary representation of the lexicon.

read(String, String) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads the learned function's binary internal represetation including both its model and lexicons from the specified files, overwriting any and all data this object may have already contained.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Reads the binary representation of a lexicon from the specified stream, overwriting the data in this object.

read(ExceptionlessInputStream, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Reads the binary representation of a lexicon from the specified stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Count

Reads the binary representation of a count into this object, overwriting any data that may already be here.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Reads the representation of a weight vector with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

Reads the representation of a weight vector with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Reads the representation of a weight vector with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Reads the representation of a weight vector with this object's run-time type from the given stream, overwriting the data in this object.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Reads the binary representation of a learner with this object's run-time type, overwriting any and all learned or manually specified parameters as well as the label lexicon but without modifying the feature lexicon.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Reads in a complete binary representation of a byte string.

read(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Reads the binary representation of a vector from the specified stream, overwriting the data in this object.

readByteString(ExceptionlessInputStream) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Reads and returns a byte string from an input stream.

readFeature(ExceptionlessInputStream) - Static method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Reads the binary representation of a feature of any type from the given stream.

readLabelLexicon(ExceptionlessInputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads the initial portion of the model file, including the containing package and name strings, the names of the labeler and extractor, and finally the label lexicon.

readLearner(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads the binary representation of any type of learner (including the label lexicon, but not including the feature lexicon) from the given file.

readLearner(String, boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads the binary representation of any type of learner (including the label lexicon, but not including the feature lexicon), with the option of cutting off the reading process after the label lexicon and before any learned parameters.

readLearner(URL) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads the binary representation of any type of learner (including the label lexicon, but not including the feature lexicon) from the given location.

readLearner(URL, boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads the binary representation of any type of learner (including the label lexicon, but not including the feature lexicon), with the option of cutting off the reading process after the label lexicon and before any learned parameters.

readLearner(ExceptionlessInputStream) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads the binary representation of any type of learner (including the label lexicon, but not including the feature lexicon) from the given stream.

readLearner(ExceptionlessInputStream, boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads the binary representation of any type of learner (including the label lexicon, but not including the feature lexicon), with the option of cutting off the reading process after the label lexicon and before any learned parameters.

readLexicon(String) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads the learned function's feature lexicon from the specified file, overwriting the lexicon present in this object, if any.

readLexicon(URL) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads the learned function's feature lexicon from the specified location, overwriting the lexicon present in this object, if any.

readLexicon(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Reads and returns a feature lexicon from the specified file.

readLexicon(URL) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Reads a feature lexicon from the specified location.

readLexicon(URL, boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Reads a feature lexicon from the specified location, with the option to ignore the feature counts by setting the second argument to false.

readLexicon(ExceptionlessInputStream) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Reads a feature lexicon from the specified stream.

readLexicon(ExceptionlessInputStream, boolean) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Reads a feature lexicon from the specified stream, with the option to ignore the feature counts by setting the second argument to false.

readLexiconOnDemand - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Informs this learner that it can and should read its feature lexicon on demand.

readLexiconOnDemand(String) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Prepares this learner to read in its feature lexicon from the specified location on demand; has no effect if this learner already has a non-empty lexicon.

readLexiconOnDemand(URL) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Prepares this learner to read in its feature lexicon from the specified location on demand; has no effect if this learner already has a non-empty lexicon.

readLine() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.LineByLine

Reads a line from the current buffer and returns it.

readModel(String) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads only the learned function's model and label lexicon from the specified file in binary form, overwriting whatever model data may have already existed in this object.

readModel(URL) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Reads only the learned function's model and label lexicon from the specified location in binary form, overwriting whatever model data may have already existed in this object.

readParameters(URL) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Deserializes a Learner.Parameters object out of the specified locaiton.

readPrunedSize(ExceptionlessInputStream) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Reads the value of Lexicon.pruneCutoff from the specified stream, discarding everything else.

readWeightVector(ExceptionlessInputStream) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Reads the binary representation of a weight vector of any type from the given stream.

REAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

REAL - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Value of the type variable.

REAL_ARRAY - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Value of the type variable.

REAL_GENERATOR - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Value of the type variable.

RealArrayFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A real array feature keeps track of its index in the classifier's returned array.

RealArrayFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

For internal use only.

RealArrayFeature(String, String, ByteString, double, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Sets all member variables.

RealArrayStringFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A real array feature keeps track of its index in the classifier's returned array.

RealArrayStringFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

For internal use only.

RealArrayStringFeature(String, String, String, double, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Sets all member variables.

realCache - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Caches the result of the FeatureVector.makeReal() method.

RealConjunctiveFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

Represents the conjunction of two features.

RealConjunctiveFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

For internal use only.

RealConjunctiveFeature(Classifier, Feature, Feature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Creates a new conjunctive feature taking the package and name of the given classifier.

RealConjunctiveFeature(String, String, Feature, Feature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Creates a new conjunctive feature.

RealFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A real feature takes on any value representable by a double.

RealFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealFeature

For internal use only.

RealFeature(String, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealFeature

Sets both the identifier and the value.

RealPrimitiveFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A real feature takes on any value representable by a double.

RealPrimitiveFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

For internal use only.

RealPrimitiveFeature(String, String, ByteString, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Sets both the identifier and the value.

RealPrimitiveStringFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A real feature takes on any value representable by a double.

RealPrimitiveStringFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

For internal use only.

RealPrimitiveStringFeature(String, String, String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Sets both the identifier and the value.

RealReferrer - Class in edu.illinois.cs.cogcomp.lbjava.classify

A referring real feature is one that has its own identifier, but whose value comes from a separate feature that it refers to.

RealReferrer() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

For internal use only.

RealReferrer(Classifier, RealFeature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Sets both the identifier and the referent.

RealReferrer(String, String, RealFeature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Sets both the identifier and the referent.

RealReferringFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A referring real feature is one that has its own identifier, but whose value comes from a separate feature that it refers to.

RealReferringFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

For internal use only.

RealReferringFeature(Classifier, ByteString, RealFeature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Sets both the identifier and the referent.

RealReferringFeature(String, String, ByteString, RealFeature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Sets both the identifier and the referent.

RealReferringStringFeature - Class in edu.illinois.cs.cogcomp.lbjava.classify

A referring real feature is one that has its own identifier, but whose value comes from a separate feature that it refers to.

RealReferringStringFeature() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

For internal use only.

RealReferringStringFeature(Classifier, String, RealFeature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Sets both the identifier and the referent.

RealReferringStringFeature(String, String, String, RealFeature) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Sets both the identifier and the referent.

realValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Returns the value of the real feature that would be returned by this classifier.

realValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Simply computes the dot product of the weight vector and the example

realValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the value of the real prediction that this learner would make, given an example.

realValue(FeatureVector) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the value of the real prediction that this learner would make, given a feature vector.

realValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Returns the value of the real feature that would be returned by this classifier.

realValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Returns the value of the real feature that would be returned by this classifier.

realValue(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Simply computes the dot product of the weight vector and the example

realValueArray(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Returns the values of the real array of features that would be returned by this classifier.

realValueArray() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns all the values of the features in this vector (not labels) arranged in a double array.

reduce_table() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Access to reduce_goto table.

ReferenceType - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a type defined by a class.

ReferenceType(Name) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ReferenceType

Initializing constructor.

referent - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

The feature being referred to.

referent - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

The feature being referred to.

referent - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierName

(¬ø) The name as it appears in the source code.

regularisedBetaFunction(double, double, double) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.StudentT

Regularised Incomplete Beta function.

remove(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.infer.InferenceManager

Removes the inference object with the given name.

remove(int) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Replaces the children array with a new array containing all the same elements except the element with the given index.

remove() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List.NodeListIterator

Removes from the list the last element that was returned by next() or previous.

remove(Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Removes the mapping for the given feature from this lexicon and returns the feature object representing it that was stored here.

remove(int) - Method in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

Removes the child at the specified index.

remove(int) - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Removes the element at the specified index of the vector.

removeFromChildLexicon(ChildLexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Takes care of any feature-type-specific tasks that need to be taken care of when removing a feature of this type from a ChildLexicon, in particular updating parent counts and removing children of this feature if necessary.

removeFromChildLexicon(ChildLexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Takes care of any feature-type-specific tasks that need to be taken care of when removing a feature of this type from a ChildLexicon, in particular updating parent counts and removing children of this feature if necessary.

removeFromChildLexicon(ChildLexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Takes care of any feature-type-specific tasks that need to be taken care of when removing a feature of this type from a ChildLexicon, in particular updating parent counts and removing children of this feature if necessary.

removeFromChildLexicon(ChildLexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Takes care of any feature-type-specific tasks that need to be taken care of when removing a feature of this type from a ChildLexicon, in particular updating parent counts and removing children of this feature if necessary.

removeFromChildLexicon(ChildLexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Takes care of any feature-type-specific tasks that need to be taken care of when removing a feature of this type from a ChildLexicon, in particular updating parent counts and removing children of this feature if necessary.

removeNull(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Removes a label from the set of "null" labels.

replacer - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEquality

This object provides the implementation of the method that replaces the values and variables in an equality given new settings of the quantification variables; if this member variable is set to null, it means this FirstOrderEquality is not nested in a quantification.

replacer - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifiedConstraintInvocation

The implementation of the function that computes the parameter.

replacer - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.Quantifier

The implementation of the functions that compute any parameters this quantifier may have.

reportAll(TestDiscrete) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Report all the predictions in the argument's histograms.

reportError(int, String) - Static method in class edu.illinois.cs.cogcomp.lbjava.Pass

This method prints the given error message and sets the fatalError variable.

reportPrediction(String, String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Whenever a prediction is made, report that prediction and the correct label with this method.

reportPrediction(double, double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.TestReal

Update internal book keeping of each prediction and gold

reportWarning(int, String) - Static method in class edu.illinois.cs.cogcomp.lbjava.Pass

This method simply prints the given warning message.

representationTable - Static variable in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

The keys of this map are the names of Classifiers; the values are ASTNodes representing the source code implementations of the associated Classifiers.

reset() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

This method clears the all constraints and variables out of the ILP solver's problem representation, bringing the ILPSolver instance back to the state it was in when first constructed.

reset() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

This method clears the all constraints and variables out of the problem representation, bringing it back to the state it was in when first constructed.

reset() - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexInputStream

Repositions this stream to the position at the time the mark method was last called on this input stream.

reset() - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexStringInputStream

Repositions this stream to the position at the time the mark method was last called on this input stream.

reset() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNodeIterator

Restarts the iterator.

reset() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List.NodeListIterator

Restarts the iterator.

reset() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

Resets the example file stream to the beginning.

reset() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayParser

Resets the ArrayParser.index pointer to 0.

reset() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.ChildrenFromVectors

Sets this parser back to the beginning of the raw data.

reset() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Sets this parser back to the beginning of the raw data.

reset() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.LineByLine

Sets this parser back to the beginning of the raw data.

reset() - Method in interface edu.illinois.cs.cogcomp.lbjava.parse.Parser

Sets this parser back to the beginning of the raw data.

RETURN - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

returnIndex - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Used during ILP constraint generation.

returnNegation - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Used during ILP constraint generation.

ReturnStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a return statement.

ReturnStatement(Expression, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ReturnStatement

Full constructor.

returnType - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

(¬ø) The return type of the classifier.

returnType - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpression

The return type of the declared classifier.

REVISED - Static variable in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Constant representing the "revised" revision status.

RevisionAnalysis - Class in edu.illinois.cs.cogcomp.lbjava

To be run after SemanticAnalysis, this pass determines which CodeGenerators need to have their code generated and which classifiers need to be trained based on the revisions made to the LBJava source file.

RevisionAnalysis(AST) - Constructor for class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Instantiates a pass that runs on an entire AST.

revisionStatus - Static variable in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Keeps track of the names of classifiers whose revision status has been resolved.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

The other feature argument.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

The other feature argument.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderBinaryConstraint

The constraint on the right of the operator.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityTwoValues

The value on the right of the equality.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithValue

The value on the right of the equality.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithVariable

The classifier application on the right of the equality.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalBinaryConstraint

The constraint on the right of the operator.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Assignment

(¬ø) The right hand side of the assignment.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryConstraintExpression

(¬ø) The right hand side of the binary expression.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryExpression

(¬ø) The right hand side of the binary expression.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Conjunction

(¬ø) The right hand side of the conjunction.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

(¬ø) The expression on the right hand side of the operator.

right - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InstanceofExpression

(¬ø) The expression on the right hand side of instanceof.

rightConstant - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.EqualityArgumentReplacer

This flag is set if the right hand side of the equality is not quantified.

rightIsDiscreteLearner - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

Filled in by SemanticAnalysis, this flag is set if right represents the invocation of a discrete learner.

rightIsQuantified - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

Filled in by SemanticAnalysis, this flag is set if right contains any quantified variables.

rjust(String, int) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Returns a space-padded string of at least the specified width such that the argument string is right-justified within the returned string.

root - Variable in class edu.illinois.cs.cogcomp.lbjava.Pass

A reference to the root node of the AST over which this pass will operate.

ROUNDS - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

rounds - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Represents the number training repetitions; used only by the from clause.

rounds - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) Represents the integer number of training repetitions; augments the from clause.

rounds - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost.Parameters

The number of times the weak learner will be called.

rounds - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

The number of times the weak learner will be called.

rounds - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.Learner.Parameters

The number of rounds of training; but wait; this parameter doesn't actually affect the behavior of any learners as the number of training rounds is specified via other mechanisms.

rows() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Returns the number of constraints in the ILP problem.

RPAREN - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

RSHIFT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

RSHIFTEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

run(AST) - Method in class edu.illinois.cs.cogcomp.lbjava.ClassifierCSE

Runs this pass on all nodes of the indicated type.

run(ClassifierAssignment) - Method in class edu.illinois.cs.cogcomp.lbjava.ClassifierCSE

Runs this pass on all nodes of the indicated type.

run(ClassifierCastExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.ClassifierCSE

Runs this pass on all nodes of the indicated type.

run(CodedClassifier) - Method in class edu.illinois.cs.cogcomp.lbjava.ClassifierCSE

Runs this pass on all nodes of the indicated type.

run(CompositeGenerator) - Method in class edu.illinois.cs.cogcomp.lbjava.ClassifierCSE

Runs this pass on all nodes of the indicated type.

run(Conjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.ClassifierCSE

Runs this pass on all nodes of the indicated type.

run(InferenceInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.ClassifierCSE

Runs this pass on all nodes of the indicated type.

run(LearningClassifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.ClassifierCSE

Runs this pass on all nodes of the indicated type.

run(ConstraintDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.ClassifierCSE

Runs this pass on all nodes of the indicated type.

run(InferenceDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.ClassifierCSE

Runs this pass on all nodes of the indicated type.

run(AST) - Method in class edu.illinois.cs.cogcomp.lbjava.Clean

Runs this pass on all nodes of the indicated type.

run(ClassifierName) - Method in class edu.illinois.cs.cogcomp.lbjava.Clean

Runs this pass on all nodes of the indicated type.

run(CodedClassifier) - Method in class edu.illinois.cs.cogcomp.lbjava.Clean

Runs this pass on all nodes of the indicated type.

run(CompositeGenerator) - Method in class edu.illinois.cs.cogcomp.lbjava.Clean

Runs this pass on all nodes of the indicated type.

run(Conjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.Clean

Runs this pass on all nodes of the indicated type.

run(InferenceInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.Clean

Runs this pass on all nodes of the indicated type.

run(LearningClassifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Clean

Runs this pass on all nodes of the indicated type.

run(ConstraintDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.Clean

Runs this pass on all nodes of the indicated type.

run(InferenceDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.Clean

Runs this pass on all nodes of the indicated type.

run(DeclarationList) - Method in class edu.illinois.cs.cogcomp.lbjava.DeclarationNames

Runs this pass on all nodes of the indicated type.

run() - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

The main interface: call this method to apply the pass to the AST.

run(AST) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(PackageDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ImportDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(BinaryExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(InstanceCreationExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ParameterSet) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(InstanceofExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ArrayCreationExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ArrayInitializer) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(Conditional) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(LearningClassifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(CastExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(IncrementExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(Assignment) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(Constant) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(UnaryExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(Name) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(FieldAccess) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(SubscriptVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(Argument) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(Operator) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(NameList) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ConstantList) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(StatementList) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ImportList) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(DeclarationList) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ExpressionList) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ClassifierType) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ConstraintType) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(InferenceType) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(NormalizerType) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ReferenceType) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ArrayType) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(PrimitiveType) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ClassifierReturnType) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ClassifierExpressionList) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ClassifierAssignment) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ClassifierName) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ClassifierCastExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(Conjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(CodedClassifier) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(CompositeGenerator) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(InferenceInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(VariableDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(EmptyStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(LabeledStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(IfStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(SwitchStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(SwitchBlock) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(SwitchGroupList) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(SwitchGroup) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(SwitchLabelList) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(SwitchLabel) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(DoStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(WhileStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ForStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ExpressionStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ContinueStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ReturnStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(SenseStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ThrowStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(SynchronizedStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(TryStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(CatchList) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(Block) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(CatchClause) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(AssertStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(BreakStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(MethodInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(AtLeastQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(AtMostQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(BinaryConstraintExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ConstraintDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ConstraintEqualityExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ConstraintInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ConstraintStatementExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(ExistentialQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(InferenceDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(InferenceDeclaration.HeadFinder) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(InferenceDeclaration.NormalizerDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(NegatedConstraintExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(UniversalQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

One of the recursive "helper" methods for run().

run(AST) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(PackageDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ImportDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(Name) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(BinaryExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(InstanceCreationExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(InstanceofExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ArrayCreationExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ArrayInitializer) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(Conditional) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(LearningClassifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(CastExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(IncrementExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(Assignment) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(Constant) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(UnaryExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ParameterSet) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(FieldAccess) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(SubscriptVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(Argument) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(Operator) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(NameList) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ConstantList) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(StatementList) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ExpressionList) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ClassifierType) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ReferenceType) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ArrayType) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(PrimitiveType) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ClassifierReturnType) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ClassifierAssignment) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(VariableDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(EmptyStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(LabeledStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(IfStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(SwitchStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(SwitchBlock) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(SwitchGroupList) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(SwitchGroup) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(SwitchLabelList) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(SwitchLabel) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(DoStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(WhileStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ForStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ExpressionStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ContinueStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ReturnStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(SenseStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ThrowStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(SynchronizedStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(TryStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(CatchList) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(Block) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(CatchClause) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(AssertStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(BreakStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(MethodInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(DeclarationList) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ClassifierCastExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ClassifierExpressionList) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ClassifierName) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(CodedClassifier) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(CompositeGenerator) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(Conjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ImportList) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(AtLeastQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(AtMostQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(BinaryConstraintExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ConstraintDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ConstraintEqualityExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ConstraintInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ConstraintStatementExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(ExistentialQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(InferenceDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(InferenceDeclaration.HeadFinder) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(InferenceDeclaration.NormalizerDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(InferenceInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(NegatedConstraintExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(UniversalQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.PrintAST

Runs this pass on all nodes of the indicated type.

run(DeclarationList) - Method in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Runs this pass on all nodes of the indicated type.

run(LearningClassifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Runs this pass on all nodes of the indicated type.

run(ClassifierName) - Method in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Runs this pass on all nodes of the indicated type.

run(CodedClassifier) - Method in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Runs this pass on all nodes of the indicated type.

run(CompositeGenerator) - Method in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Runs this pass on all nodes of the indicated type.

run(Conjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Runs this pass on all nodes of the indicated type.

run(InferenceInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Runs this pass on all nodes of the indicated type.

run(ConstraintDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Runs this pass on all nodes of the indicated type.

run(InferenceDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Runs this pass on all nodes of the indicated type.

run(AST) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(PackageDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ImportDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(DeclarationList) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ClassifierAssignment) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ClassifierCastExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ClassifierName) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(CodedClassifier) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(CompositeGenerator) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(Conjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(InferenceInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(LearningClassifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ParameterSet) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(Block) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(MethodInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(InstanceCreationExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(Name) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ForStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(IfStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ReturnStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(SenseStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(WhileStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(DoStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(VariableDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(Argument) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(Constant) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ReferenceType) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ClassifierReturnType) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ConstraintDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ConstraintStatementExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(UniversalQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ExistentialQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(AtLeastQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(AtMostQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ConstraintInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(ConstraintEqualityExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(InferenceDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(InferenceDeclaration.HeadFinder) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(InferenceDeclaration.NormalizerDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Runs this pass on all nodes of the indicated type.

run(AST) - Method in class edu.illinois.cs.cogcomp.lbjava.Train

Runs this pass on all nodes of the indicated type.

run(LearningClassifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.Train

Runs this pass on all nodes of the indicated type.

run(CodedClassifier) - Method in class edu.illinois.cs.cogcomp.lbjava.Train

Runs this pass on all nodes of the indicated type.

run(ConstraintDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.Train

Runs this pass on all nodes of the indicated type.

run(InferenceDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.Train

Runs this pass on all nodes of the indicated type.

run() - Method in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

Performs the training and then generates the new code.

run(AST) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ClassifierName) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Code is only generated for a ClassifierName when it is the only ClassifierExpression on the right hand side of the arrow (and there really shouldn't be a reason that a programmer would want to write such a declaration, but if he does, it will work).

run(CodedClassifier) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Generates code for all nodes of the indicated type.

run(CompositeGenerator) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Generates code for all nodes of the indicated type.

run(InferenceInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Generates code for all nodes of the indicated type.

run(LearningClassifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Generates code for all nodes of the indicated type.

run(Conjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Generates code for all nodes of the indicated type.

run(ConstraintDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Generates code for all nodes of the indicated type.

run(InferenceDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Generates code for all nodes of the indicated type.

run(InferenceDeclaration.HeadFinder) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(Block) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(StatementList) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(AssertStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(BreakStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ContinueStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ExpressionStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ForStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(IfStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(LabeledStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ReturnStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(SenseStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(SwitchStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(SynchronizedStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ThrowStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(TryStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(VariableDeclaration) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(WhileStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(DoStatement) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(SwitchGroupList) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(SwitchGroup) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(SwitchLabelList) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(SwitchLabel) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(CatchList) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(CatchClause) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(Argument) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ConstraintStatementExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(BinaryConstraintExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(NegatedConstraintExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ConstraintEqualityExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ConstraintInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(UniversalQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ExistentialQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(AtLeastQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(AtMostQuantifierExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ExpressionList) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ArrayCreationExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ArrayInitializer) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(CastExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(Conditional) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(Constant) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ParameterSet) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(InstanceofExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(Assignment) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(IncrementExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(InstanceCreationExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(MethodInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(BinaryExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(UnaryExpression) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(FieldAccess) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(SubscriptVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(Name) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ArrayType) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(PrimitiveType) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(ReferenceType) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

run(Operator) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Runs this pass on all nodes of the indicated type.

runAndRestore(AST) - Static method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Running an instance of this pass overwrites the static member variables; use this method to run an instance of this pass and then restore the static member variables to their states before the pass was run.

runJavac(String) - Static method in class edu.illinois.cs.cogcomp.lbjava.Train

Run the javac compiler with the specified arguments in addition to those specified on the command line.

runOnChildren(ASTNode) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

This method supports derived passes that continue to descend down the AST after operating on a particular type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Argument

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayCreationExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayInitializer

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayType

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AssertStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Assignment

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AST

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNode

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AtLeastQuantifierExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AtMostQuantifierExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryConstraintExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Block

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BreakStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CastExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchClause

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchList

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierCastExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpressionList

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierName

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CodedClassifier

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CompositeGenerator

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conditional

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conjunction

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Constant

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintDeclaration

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintInvocation

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintStatementExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintType

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ContinueStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DeclarationList

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DoStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.EmptyStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExistentialQuantifierExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.FieldAccess

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.IfStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportDeclaration

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportList

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.IncrementExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.HeadFinder

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.NormalizerDeclaration

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceInvocation

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InstanceCreationExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InstanceofExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LabeledStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Name

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NameList

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NegatedConstraintExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NormalizerType

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PackageDeclaration

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReferenceType

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReturnStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.StatementList

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SubscriptVariable

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroup

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroupList

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabel

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabelList

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SynchronizedStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ThrowStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.TryStatement

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.UnaryExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.UniversalQuantifierExpression

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

Ensures that the correct run() method is called for this type of node.

runPass(Pass) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.WhileStatement

Ensures that the correct run() method is called for this type of node.

runSemanticAnalysis(AST) - Static method in class edu.illinois.cs.cogcomp.lbjava.Main

Runs the semantic analysis pass on the specified AST, then prints errors and warnings if they exist, and finally sets the Main.generatedSourceDirectory and Main.classDirectory variables.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.AtLeastQuantifier

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.AtMostQuantifier

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Constraint

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ExistentialQuantifier

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConjunction

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConstant

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDisjunction

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderDoubleImplication

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityTwoValues

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithValue

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithVariable

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderImplication

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNegation

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifiedConstraintInvocation

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

runVisit(Inference) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.UniversalQuantifier

Calls the appropriate visit(·) method of the given Inference for this Constraint, as per the visitor pattern.

S

satisfied() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Determines if the constraints are satisfied by the current variable assignments.

save() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Writes the binary representation of this learned function if there is a location cached in Learner.lcFilePath, and writes the binary representation of the feature lexicon if there is a location cached in Learner.lexFilePath.

saveLexicon() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Writes the binary representation of the feature lexicon to the location specified by Learner.lexFilePath.

saveModel() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Writes the binary representation of this learned function to the location specified by Learner.lcFilePath.

scaledAdd(int[], double[], double, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedRandomWeightVector

Self-modifying vector addition where the argument vector is first scaled by the given factor.

scaledAdd(int[], double[], double, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

Self-modifying vector addition where the argument vector is first scaled by the given factor.

scaledAdd(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

This method is similar to the implementation in SparseWeightVector except that NaiveBayes.NaiveBayesVector.incrementCount(int,double) is called instead of SparseWeightVector.setWeight(int,double).

scaledAdd(int[], double[], double, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

This method is similar to the implementation in SparseWeightVector except that the defaultW argument is ignored and NaiveBayes.NaiveBayesVector.incrementCount(int,double) is called instead of SparseWeightVector.setWeight(int,double).

scaledAdd(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Performs pairwise addition of the feature values in the given vector scaled by the given factor, modifying this weight vector, using the specified default weight when a feature from the given vector is not yet present in this vector.

scaledAdd(int[], double[], double, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Performs pairwise addition of the feature values in the given vector scaled by the given factor, modifying this weight vector, using the specified default weight when a feature from the given vector is not yet present in this vector.

scaledAdd(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Self-modifying vector addition.

scaledAdd(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Self-modifying vector addition where the argument vector is first scaled by the given factor.

scaledAdd(int[], double[], double, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Self-modifying vector addition where the argument vector is first scaled by the given factor.

scaledMultiply(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Self-modifying vector multiplication where the argument vector is first scaled by the given factor.

scaledMultiply(int[], double[], double, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Self-modifying vector multiplication where the argument vector is first scaled by the given factor.

Score - Class in edu.illinois.cs.cogcomp.lbjava.classify

A score is a number produced by a learner that indicates the degree to which a particular discrete classification is appropriate for a given object.

Score(String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.Score

Initializes both member variables.

score - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.Score

The score.

score(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Computes the score for the specified example vector which will be thresholded to make the binary classification.

score(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Computes the score for the specified example vector which will be thresholded to make the binary classification.

score(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

The score of the specified object is equal to w * x + bias where * is dot product, w is the weight vector, and x is the feature vector produced by the extractor.

score(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Computes the dot product of the specified example vector and the weight vector associated with the supplied class.

score(Object, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Computes the dot product of the specified example vector and the weight vector associated with the supplied class.

score(int[], double[], int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Computes the dot product of the specified feature vector and the weight vector associated with the supplied class.

scores(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Produces a set of scores indicating the degree to which each possible discrete classification value is associated with the given example object.

scores(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Produces a set of scores indicating the degree to which each possible discrete classification value is associated with the given example object.

scores(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Produces a set of scores indicating the degree to which each possible discrete classification value is associated with the given example object.

scores(FeatureVector) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Produces a set of scores indicating the degree to which each possible discrete classification value is associated with the given feature vector.

scores(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Produces a set of scores indicating the degree to which each possible discrete classification value is associated with the given example object.

scores(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

An LTU returns two scores; one for the negative classification and one for the positive classification.

scores(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Produces a set of scores indicating the degree to which each possible discrete classification value is associated with the given example object.

scores(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

The scores in the returned ScoreSet are the posterior probabilities of each possible label given the example.

scores(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Produces a set of scores indicating the degree to which each possible discrete classification value is associated with the given example object.

scores(Object, Collection) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Returns scores for only those labels in the given collection.

scores(int[], double[], Collection) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Returns scores for only those labels in the given collection.

scores(Object, Collection) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Returns scores for only those labels in the given collection.

scores(int[], double[], Collection) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Returns scores for only those labels in the given collection.

scores(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Produces a set of scores indicating the degree to which each possible discrete classification value is associated with the given example object.

scores(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Since this algorithm returns a real feature, it does not return scores.

scores(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

An SVM returns a classification score for each class.

scores(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Produces a set of scores indicating the degree to which each possible discrete classification value is associated with the given example object.

scoresAugmented(Object, ScoreSet) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Update the score of each binary variable (label) based on the gold value of each example for that variable.

ScoreSet - Class in edu.illinois.cs.cogcomp.lbjava.classify

A score set is simply a set of Scores.

ScoreSet() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.ScoreSet

Default constructor.

ScoreSet(String[], double[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.ScoreSet

The elements of the two argument arrays are assumed to be pair-wise associated with each other.

ScoreSet(Score[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.ScoreSet

The elements of the array are added to the set.

SemanticAnalysis - Class in edu.illinois.cs.cogcomp.lbjava

The SemanticAnalysis pass builds useful tables, computes classifier types and other useful information, and generally checks that things appear only where they are expected.

SemanticAnalysis() - Constructor for class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Default constructor.

SemanticAnalysis(AST) - Constructor for class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Instantiates a pass that runs on an entire AST.

SEMICOLON - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

SENSE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

SENSEALL - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

senseall - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

true iff this is a senseall statement.

SenseStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a feature sensing statement.

SenseStatement(Expression, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

Initializing constructor.

SenseStatement(Expression, boolean, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

Initializing constructor.

SenseStatement(Expression, Expression, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

Initializing constructor.

SenseStatement(Expression, Expression, boolean, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

Full constructor.

senseValueChild() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Expression

Supports the SemanticAnalysis pass which needs to notify MethodInvocations that are the immediate value child of a SenseStatement that it's allowable to invoke an array or generator classifier.

senseValueChild() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Sets the isSensedValue flag.

separator - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.List

The characters appearing in between elements of the list in its string representation.

separator - Static variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldSeparator

The only instance of this class is stored here.

sequential - Static variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser.SplitPolicy

Represents the sequential split policy.

set(ASTNode) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List.NodeListIterator

Replaces the last element returned by next() or previous() with the specified element.

set(int, Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Sets the value at the specified index to the given value.

set(int, Feature, Feature) - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Sets the value at the specified index to the given value.

setArrayLength(int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

If this feature is an array feature, call this method to set its array length; otherwise, this method has no effect.

setArrayLength(int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

If this feature is an array feature, call this method to set its array length; otherwise, this method has no effect.

setArrayLength(int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

If this feature is an array feature, call this method to set its array length; otherwise, this method has no effect.

setArrayLength(int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

If this feature is an array feature, call this method to set its array length; otherwise, this method has no effect.

setArrayLength(int) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

If this feature is an array feature, call this method to set its array length; otherwise, this method has no effect.

setBase(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Sets MuxLearner.baseLearner.

setBeta(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Sets the BinaryMIRA.beta member variable to the specified value.

setBeta(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Sets the SparseWinnow.beta member variable to the specified value.

setBoundType(int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Sets the bound type for the specified constraint.

setCacheIn(Name) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierCastExpression

Sets the cacheIn member variable to the argument.

setCacheIn(Name) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpression

Sets the cacheIn member variable to the argument.

setCandidates(int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

setConfidence(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Sets the SparseConfidenceWeighted.confidence member variable to the specified value.

setConstraintBound(int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Sets the bound on the specified constraint.

setConstraintCoefficient(int, int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Sets the specified coefficient in the constraint matrix.

setCurrentCG(CodeGenerator) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Sets the current code generator for this translator.

setDefaultFeature() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Sets the value of MuxLearner.defaultFeature according to the current value of MuxLearner.defaultPrediction.

setEncoding(String) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Sets the encoding to use in this learner's feature lexicon.

setEncoding(String) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Sets the encoding used when adding features to this lexicon.

setExample(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderVariable

Sets the example object.

setExtractor(Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Sets the extractor.

setExtractor(Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Sets the extractor.

setFirst(boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Sets the value of BalasHook.first.

setFromPivot(boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Sets the value of FoldParser.fromPivot, which controls whether examples will be taken from the pivot fold or from all other folds.

setIncludePruned(boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

Setter for ArrayFileParser.includePruned.

setIndent(int) - Method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Sets the indentation level.

setInitialVariance(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Sets the SparseConfidenceWeighted.initialVariance member variable to the specified value.

setInitialWeight(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Sets the LinearThresholdUnit.initialWeight member variable to the specified value.

setIsTraining(boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Sets the static isTraining flag inside BatchTrainer.learner's runtime class to the specified value.

setLabeler(Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ValueComparer

Sets the value of ValueComparer.labeler.

setLabeler(Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Sets the labeler.

setLabeler(Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Sets the labeler.

setLabeler(Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Sets the labels list.

setLabeler(Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Sets the labeler.

setLabeler(Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Sets the labeler.

setLabeler(Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Sets the labeler.

setLabeler(Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Sets the labeler.

setLabeler(Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Sets the labels list.

setLabeler(Classifier) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Sets the labeler.

setLabelLexicon(Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Sets the label lexicon.

setLabelLexicon(Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Sets the label lexicon.

setLearningRate(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Sets the LinearThresholdUnit.learningRate member variable to the specified value.

setLearningRate(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Sets the LinearThresholdUnit.learningRate member variable to the specified value.

setLearningRate(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Sets the StochasticGradientDescent.learningRate member variable to the specified value.

setLexicon(Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Sets the feature lexicon.

setLexiconLocation(String) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Sets the location of the lexicon as a regular file on this file system.

setLexiconLocation(URL) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Sets the location of the model as a URL.

setLossFlag() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

setLTU(LinearThresholdUnit) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Sets the baseLTU variable.

setMaximize(boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Sets the direction of the objective function.

setModelLocation(String) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Sets the location of the model as a regular file on this file system.

setModelLocation(URL) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Sets the location of the model as a URL.

setNegativeThickness(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Sets the LinearThresholdUnit.negativeThickness member variable to the specified value.

setNetworkLabel(int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Create a LinearThresholdUnit and add it to the network

setObjectiveCoefficient(int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Sets the specified coefficient in the objective function.

setPackage(String) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Sets the package name in the top level table.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(AdaBoost.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(AdaGrad.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(BinaryMIRA.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(Learner.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(LinearThresholdUnit.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MultiLabelLearner.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(MuxLearner.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(NaiveBayes.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(SparseAveragedPerceptron.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(SparseConfidenceWeighted.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(SparseNetworkLearner.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(SparseWinnow.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(StochasticGradientDescent.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(SupportVectorMachine.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Sets the values of parameters that control the behavior of this learning algorithm.

setParameters(Learner) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper.Parameters

Calls the appropriate Learner.setParameters(Parameters) method for this Parameters object.

setParameters(WekaWrapper.Parameters) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Sets the values of parameters that control the behavior of this learning algorithm.

setParent(Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Sets the value of ChildLexicon.parentLexicon and makes sure that any features marked for removal in this lexicon are the identical objects also present in the parent.

setPivot(int) - Method in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Sets the pivot fold, which also causes FoldParser.parser to be reset.

setPositiveThickness(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Sets the LinearThresholdUnit.positiveThickness member variable to the specified value.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ArgumentReplacer

Provides the settings of quantification variables.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.AtLeastQuantifier

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's children.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.AtMostQuantifier

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's children.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ExistentialQuantifier

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's children.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderBinaryConstraint

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's FirstOrderEquality children.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConstant

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's FirstOrderEquality children.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderConstraint

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's FirstOrderEquality children.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityTwoValues

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's FirstOrderEquality children.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithValue

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's FirstOrderEquality children.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEqualityWithVariable

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's FirstOrderEquality children.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNAryConstraint

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's FirstOrderEquality children.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNegation

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's FirstOrderEquality children.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.QuantifiedConstraintInvocation

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's FirstOrderEquality children.

setQuantificationVariables(Vector) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.UniversalQuantifier

This method sets the given quantification variables to the given object references and evaluates the expressions involving those variables in this constraint's children.

setReadLexiconOnDemand() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

setRoot(ASTNode) - Method in class edu.illinois.cs.cogcomp.lbjava.Pass

Sets the root member variable.

setSmoothing(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Sets the smoothing parameter to the specified value.

setThickness(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Sets the LinearThresholdUnit.positiveThickness and LinearThresholdUnit.negativeThickness member variables to the specified value.

setThreshold(double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Sets the LinearThresholdUnit.threshold member variable to the specified value.

setThresholds(int[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

Use this method to establish feature count thresholds in the "Percentage" policy.

setType(Type) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

Setting this declaration statement's type also sets its line and byte offset information.

setValue(String) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderVariable

Sets the value of this variable.

setValue(String) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Sets the value of this byte string to the byte encoding of the specified string.

setWeight(int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

This method is overridden to do nothing; use NaiveBayes.NaiveBayesVector.incrementCount(int,double) instead.

setWeight(int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Sets the weight of the given feature.

setWeight(int, double, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Sets the weight of the given feature.

shallow() - Method in interface edu.illinois.cs.cogcomp.lbjava.CodeGenerator

Returns a shallow textual representation of the AST node.

shallow() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierCastExpression

Creates a StringBuffer containing a shallow representation of this ASTNode.

shallow() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpression

Creates a StringBuffer containing a shallow representation of this ClassifierExpression.

shallow() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierName

Creates a StringBuffer containing a shallow representation of this ClassifierExpression.

shallow() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CodedClassifier

Creates a StringBuffer containing a shallow representation of this ASTNode.

shallow() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CompositeGenerator

Creates a StringBuffer containing a shallow representation of this ASTNode.

shallow() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conjunction

Creates a StringBuffer containing a shallow representation of this ASTNode.

shallow() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintDeclaration

Returns a shallow textual representation of this AST node.

shallow() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Returns a shallow textual representation of this AST node.

shallow() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceInvocation

Creates a StringBuffer containing a shallow representation of this ASTNode.

shallow() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Creates a StringBuffer containing a shallow representation of this ASTNode.

SHORT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

SHORT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Value of the type variable.

shortValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.MultiValueComparer

Returns the prediction of this classifier as a short that acts as a pointer into DiscreteFeature.BooleanValues.

shortValue(Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ParameterizedConstraint

Returns the prediction of this classifier as a short that acts as a pointer into DiscreteFeature.BooleanValues.

shouldDemote(boolean, double, double, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Determines if the weights should be promoted.

shouldDemote(boolean, double, double, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Determines if the weights should be demoted

shouldPromote(boolean, double, double, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Determines if the weights should be promoted.

shouldPromote(boolean, double, double, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Determines if the weights should be promoted

shuffled - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

Used only by the random splitting policy to remember which example indexes are in which folds.

shuffleIndex - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

An index pointing into FoldParser.shuffled.

Sigmoid - Class in edu.illinois.cs.cogcomp.lbjava.learn

The sigmoid normalization function replaces each score xi with 1 / (1 + exp(-alpha xi)), where alpha is a user-specified constant.

Sigmoid() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Sigmoid

Default constructor; sets Sigmoid.alpha to 1.

Sigmoid(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Sigmoid

Initializing constructor.

sign(double) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.StudentT

returns -1 if x < 0 else returns 1 (double version)

signature(Method, int, Class, String, Class[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

This method generates a string signature of the given method.

SIGNED_RIGHT_SHIFT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

SIGNED_RIGHT_SHIFT_ASSIGN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

simpleDot(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Takes the dot product of the regular, non-averaged, Perceptron weight vector with the given vector, using the hard coded default weight.

simpleDot(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Takes the dot product of the regular, non-averaged, Perceptron weight vector with the given vector, using the specified default weight when a feature is not yet present in this vector.

simplify() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Produces a new, logically simplified version of this constraint, preserving variable consolidation.

simplify() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Produces a new, logically simplified version of this constraint, preserving variable consolidation.

simplify(boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Same as simplify(), except this method gives the caller the ability to optionally leave double implications that are immediate children of this conjunction in tact.

simplify() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Produces a new, logically simplified version of this constraint, preserving variable consolidation.

simplify() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Produces a new, logically simplified version of this constraint, preserving variable consolidation.

simplify() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Produces a new, logically simplified version of this constraint, preserving variable consolidation.

simplify() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Produces a new, logically simplified version of this constraint, preserving variable consolidation.

simplify() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Produces a new, logically simplified version of this constraint, preserving variable consolidation.

simplify() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Produces a new, logically simplified version of this constraint, preserving variable consolidation.

simplify() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Produces a new, logically simplified version of this constraint, preserving variable consolidation.

singleExampleCache - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

Whether the classifier will have a single example feature vector cache.

singleExampleCache - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpression

Whether the classifier will have a single example feature vector cache.

size() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

The size of this vector is defined as the size of FeatureVector.features plus the size of FeatureVector.labels.

size() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ScoreSet

Returns the number of scores in this set.

size() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderNAryConstraint

Returns the number of terms in this constraint.

size() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Returns the number of terms in this constraint.

size() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNAryConstraint

Returns the number of terms in this constraint.

size() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List

Returns the size of the list.

size() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Returns the number of features currently stored in Lexicon.lexicon.

size() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Returns the length of the weight vector.

size() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedVector

Returns the size of the vector.

size - Variable in class edu.illinois.cs.cogcomp.lbjava.util.FVector

The number of elements in the vector.

size() - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Returns the value of FVector.size.

sizes - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayCreationExpression

(¬ø) Describes the size of each dimension in the new array.

skip(long) - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexInputStream

Skips over and discards n bytes of data from this input stream.

skip(long) - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexStringInputStream

Skips over and discards n chars of data from this input stream.

smoothing - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Parameters

The exponential of this number is used as the conditional probability of a feature that was never observed during training; default NaiveBayes.defaultSmoothing.

smoothing - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

The exponential of this number is used as the conditional probability of a feature that was never observed during training; default NaiveBayes.defaultSmoothing.

Softmax - Class in edu.illinois.cs.cogcomp.lbjava.learn

The softmax normalization function replaces each score with the fraction of its exponential out of the sum of all scores' exponentials.

Softmax() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Softmax

Default constructor; sets Softmax.alpha to 1.

Softmax(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.Softmax

Initializing constructor.

solve() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Solves the ILP problem, saving the solution internally.

solve(double) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Implements the meat of the Balas algorithm recursively.

solver - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

The ILP algorithm.

solverType - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine.Parameters

The type of solver; default SupportVectorMachine.defaultSolverType.

solverType - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

The type of solver; default SupportVectorMachine.defaultSolverType unless there are more than 2 labels observed in the training data, in which case "MCSVM_CS" becomes the default.

sort() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Sorts both of the feature lists.

sort() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List

Sorts the list according to their natural ordering.

sort(Comparator) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List

Sorts the list according to the order induced by the specified comparator.

sort() - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Sorts this vector in increasing order.

sourceDirectory - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

The relative path to the LBJava source file.

sourceFileBase - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

The source file's name without the .lbj extension.

sourceFilename - Variable in class edu.illinois.cs.cogcomp.lbjava.frontend.Yylex

sourceFilename - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

The name of the LBJava source file as specified on the command line.

sourcePath - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

The directory in which to search for source files.

SparseAveragedPerceptron - Class in edu.illinois.cs.cogcomp.lbjava.learn

An approximation to voted Perceptron, in which a weighted average of the weight vectors arrived at during training becomes the weight vector used to make predictions after training.

SparseAveragedPerceptron() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

The learning rate and threshold take default values, while the name of the classifier gets the empty string.

SparseAveragedPerceptron(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Sets the learning rate to the specified value, and the threshold takes the default, while the name of the classifier gets the empty string.

SparseAveragedPerceptron(double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Sets the learning rate and threshold to the specified values, while the name of the classifier gets the empty string.

SparseAveragedPerceptron(double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Use this constructor to fit a thick separator, where both the positive and negative sides of the hyperplane will be given the specified thickness, while the name of the classifier gets the empty string.

SparseAveragedPerceptron(double, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Use this constructor to fit a thick separator, where the positive and negative sides of the hyperplane will be given the specified separate thicknesses, while the name of the classifier gets the empty string.

SparseAveragedPerceptron(SparseAveragedPerceptron.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Initializing constructor.

SparseAveragedPerceptron(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

The learning rate and threshold take default values.

SparseAveragedPerceptron(String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Sets the learning rate to the specified value, and the threshold takes the default.

SparseAveragedPerceptron(String, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Sets the learning rate and threshold to the specified values.

SparseAveragedPerceptron(String, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Use this constructor to fit a thick separator, where both the positive and negative sides of the hyperplane will be given the specified thickness.

SparseAveragedPerceptron(String, double, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Use this constructor to fit a thick separator, where the positive and negative sides of the hyperplane will be given the specified separate thicknesses.

SparseAveragedPerceptron(String, SparseAveragedPerceptron.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Initializing constructor.

SparseAveragedPerceptron.AveragedWeightVector - Class in edu.illinois.cs.cogcomp.lbjava.learn

This implementation of a sparse weight vector associates two doubles with each Feature.

SparseAveragedPerceptron.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of SparseAveragedPerceptron's configurable parameters.

SparseConfidenceWeighted - Class in edu.illinois.cs.cogcomp.lbjava.learn

This is an implementation of the approximate "variance algorithm" of Confidence Weighted Linear Classification, Dredze, et.al (ICML, 2008).

SparseConfidenceWeighted() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

All parameters get default values.

SparseConfidenceWeighted(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Sets the SparseConfidenceWeighted.confidence parameter.

SparseConfidenceWeighted(double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Sets the SparseConfidenceWeighted.confidence and SparseConfidenceWeighted.initialVariance parameters.

SparseConfidenceWeighted(double, double, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Sets the SparseConfidenceWeighted.confidence, SparseConfidenceWeighted.initialVariance, and LinearThresholdUnit.weightVector parameters.

SparseConfidenceWeighted(double, double, SparseWeightVector, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Sets the SparseConfidenceWeighted.confidence, SparseConfidenceWeighted.initialVariance, LinearThresholdUnit.weightVector, and SparseConfidenceWeighted.variances parameters.

SparseConfidenceWeighted(SparseConfidenceWeighted.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Initializing constructor.

SparseConfidenceWeighted(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

All parameters get default values.

SparseConfidenceWeighted(String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Sets the SparseConfidenceWeighted.confidence parameter.

SparseConfidenceWeighted(String, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Sets the SparseConfidenceWeighted.confidence and SparseConfidenceWeighted.initialVariance parameters.

SparseConfidenceWeighted(String, double, double, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Sets the SparseConfidenceWeighted.confidence, SparseConfidenceWeighted.initialVariance, and LinearThresholdUnit.weightVector parameters.

SparseConfidenceWeighted(String, double, double, SparseWeightVector, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Sets the SparseConfidenceWeighted.confidence, SparseConfidenceWeighted.initialVariance, LinearThresholdUnit.weightVector, and SparseConfidenceWeighted.variances parameters.

SparseConfidenceWeighted(String, SparseConfidenceWeighted.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Initializing constructor.

SparseConfidenceWeighted.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of SparseConfidenceWeighted's configurable parameters.

SparseMIRA - Class in edu.illinois.cs.cogcomp.lbjava.learn

An implementation of the Margin Infused Relaxed Algorithm of Crammer and Singer.

SparseMIRA() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

This algorithm has no parameters to set!

SparseMIRA(SparseMIRA.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Initializing constructor.

SparseMIRA(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

This algorithm has no parameters to set!

SparseMIRA(String, SparseMIRA.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Initializing constructor.

SparseMIRA.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of SparseMIRA's configurable parameters.

SparseNetworkLearner - Class in edu.illinois.cs.cogcomp.lbjava.learn

A SparseNetworkLearner uses multiple LinearThresholdUnits to make a multi-class classification.

SparseNetworkLearner() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Instantiates this multi-class learner with the default learning algorithm: SparseNetworkLearner.defaultBaseLTU.

SparseNetworkLearner(LinearThresholdUnit) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Instantiates this multi-class learner using the specified algorithm to learn each class separately as a binary classifier.

SparseNetworkLearner(SparseNetworkLearner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Initializing constructor.

SparseNetworkLearner(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Instantiates this multi-class learner with the default learning algorithm: SparseNetworkLearner.defaultBaseLTU.

SparseNetworkLearner(String, LinearThresholdUnit) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Instantiates this multi-class learner using the specified algorithm to learn each class separately as a binary classifier.

SparseNetworkLearner(String, SparseNetworkLearner.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Initializing constructor.

SparseNetworkLearner.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of SparseNetworkLearner's configurable parameters.

SparsePerceptron - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simple sparse Perceptron implementation.

SparsePerceptron() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

The learning rate and threshold take default values, while the name of the classifier gets the empty string.

SparsePerceptron(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Sets the learning rate to the specified value, and the threshold takes the default, while the name of the classifier gets the empty string.

SparsePerceptron(double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Sets the learning rate and threshold to the specified values, while the name of the classifier gets the empty string.

SparsePerceptron(double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Use this constructor to fit a thick separator, where both the positive and negative sides of the hyperplane will be given the specified thickness, while the name of the classifier gets the empty string.

SparsePerceptron(double, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Use this constructor to fit a thick separator, where the positive and negative sides of the hyperplane will be given the specified separate thicknesses, while the name of the classifier gets the empty string.

SparsePerceptron(double, double, double, double, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Use this constructor to specify an alternative subclass of SparseWeightVector, while the name of the classifier gets the empty string.

SparsePerceptron(SparsePerceptron.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Initializing constructor.

SparsePerceptron(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

The learning rate and threshold take default values.

SparsePerceptron(String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Sets the learning rate to the specified value, and the threshold takes the default.

SparsePerceptron(String, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Sets the learning rate and threshold to the specified values.

SparsePerceptron(String, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Use this constructor to fit a thick separator, where both the positive and negative sides of the hyperplane will be given the specified thickness.

SparsePerceptron(String, double, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Use this constructor to fit a thick separator, where the positive and negative sides of the hyperplane will be given the specified separate thicknesses.

SparsePerceptron(String, double, double, double, double, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Use this constructor to specify an alternative subclass of SparseWeightVector.

SparsePerceptron(String, SparsePerceptron.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Initializing constructor.

SparsePerceptron.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of SparsePerceptron's configurable parameters.

SparseWeightVector - Class in edu.illinois.cs.cogcomp.lbjava.learn

This class is used as a weight vector in sparse learning algorithms.

SparseWeightVector() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Simply instantiates SparseWeightVector.weights.

SparseWeightVector(double[]) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Simply initializes SparseWeightVector.weights.

SparseWeightVector(DVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Simply initializes SparseWeightVector.weights.

SparseWinnow - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simple sparse Winnow implementation.

SparseWinnow() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

LinearThresholdUnit.learningRate, SparseWinnow.beta, and LinearThresholdUnit.threshold take default values, while the name of the classifier gets the empty string.

SparseWinnow(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Sets LinearThresholdUnit.learningRate to the specified value, SparseWinnow.beta to 1 / LinearThresholdUnit.learningRate , and the LinearThresholdUnit.threshold takes the default, while the name of the classifier gets the empty string.

SparseWinnow(double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Sets LinearThresholdUnit.learningRate and SparseWinnow.beta to the specified values, and the LinearThresholdUnit.threshold takes the default, while the name of the classifier gets the empty string.

SparseWinnow(double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Sets LinearThresholdUnit.learningRate, SparseWinnow.beta, and LinearThresholdUnit.threshold to the specified values, while the name of the classifier gets the empty string.

SparseWinnow(double, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Use this constructor to fit a thick separator, where both the positive and negative sides of the hyperplane will be given the specified thickness, while the name of the classifier gets the empty string.

SparseWinnow(double, double, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Use this constructor to fit a thick separator, where the positive and negative sides of the hyperplane will be given the specified separate thicknesses, while the name of the classifier gets the empty string.

SparseWinnow(double, double, double, double, double, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Use this constructor to specify an alternative subclass of SparseWeightVector, while the name of the classifier gets the empty string.

SparseWinnow(SparseWinnow.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Initializing constructor.

SparseWinnow(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

LinearThresholdUnit.learningRate, SparseWinnow.beta, and LinearThresholdUnit.threshold take default values.

SparseWinnow(String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Sets LinearThresholdUnit.learningRate to the specified value, SparseWinnow.beta to 1 / LinearThresholdUnit.learningRate , and the LinearThresholdUnit.threshold takes the default.

SparseWinnow(String, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Sets LinearThresholdUnit.learningRate and SparseWinnow.beta to the specified values, and the LinearThresholdUnit.threshold takes the default.

SparseWinnow(String, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Sets LinearThresholdUnit.learningRate, SparseWinnow.beta, and LinearThresholdUnit.threshold to the specified values.

SparseWinnow(String, double, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Use this constructor to fit a thick separator, where both the positive and negative sides of the hyperplane will be given the specified thickness.

SparseWinnow(String, double, double, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Use this constructor to fit a thick separator, where the positive and negative sides of the hyperplane will be given the specified separate thicknesses.

SparseWinnow(String, double, double, double, double, double, SparseWeightVector) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Use this constructor to specify an alternative subclass of SparseWeightVector.

SparseWinnow(String, SparseWinnow.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Initializing constructor.

SparseWinnow.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of SparseWinnow's configurable parameters.

splitPolicy - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Dictates how the training data will be split into subsets for use by cross validation.

splitPolicy - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) Dictates how the training data will be split into subsets for use by cross validation; second argument to cval.

splitPolicy - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

The way in which examples are partitioned into folds.

start - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

The start value for the range.

start - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.LinkedChild

The offset into the raw data input file at which this child starts.

start_production() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Indicates start production.

start_state() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Indicates start state.

startingRound - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Training starts from this round number.

statement - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LabeledStatement

(¬ø) The statement.

Statement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Abstract class from which statements are derived.

StatementExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

Abstract class for representing expressions that can stand alone as a statement.

statementList() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Block

Returns the statement list.

StatementList - Class in edu.illinois.cs.cogcomp.lbjava.IR

Currently, this is just a wrapper class for LinkedList.

StatementList() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.StatementList

Default constructor.

StatementList(int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.StatementList

Initializing constructor.

StatementList(Statement) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.StatementList

Initializing constructor.

StatementList.StatementListIterator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Used to iterate though the children of a list of AST nodes.

StatementListIterator() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.StatementList.StatementListIterator

statements - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroup

(¬ø) The list of statements in the group.

STATIC - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

statusNames - Static variable in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

The names of the three revision states.

statusToString(Integer) - Static method in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Returns the name of a revision status, or "no status" if the status is null.

stddev - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

The random numbers that are generated by this class are Gaussian with mean 0 and standard deviation defined by this variable.

StochasticGradientDescent - Class in edu.illinois.cs.cogcomp.lbjava.learn

Gradient descent is a batch learning algorithm for function approximation in which the learner tries to follow the gradient of the error function to the solution of minimal error.

StochasticGradientDescent() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

The learning rate takes the default value, while the name of the classifier gets the empty string.

StochasticGradientDescent(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Sets the learning rate to the specified value, while the name of the classifier gets the empty string.

StochasticGradientDescent(StochasticGradientDescent.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Initializing constructor.

StochasticGradientDescent(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

The learning rate takes the default value.

StochasticGradientDescent(String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Use this constructor to specify an alternative subclass of SparseWeightVector.

StochasticGradientDescent(String, StochasticGradientDescent.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Initializing constructor.

StochasticGradientDescent.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of StochasticGradientDescent's configurable parameters.

StudentT - Class in edu.illinois.cs.cogcomp.lbjava.util

A collection of statistical methods supporting computations related to the Student's T distribution.

StudentT() - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.StudentT

studentTcdf(double, int) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.StudentT

Returns the Student's t cumulative distribution function probability

subexpression - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.IncrementExpression

(¬ø) The expression on which the increment operator operates.

subexpression - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.UnaryExpression

(¬ø) The expression on which the unary operator operates.

SUBJECTTO - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

SUBJECTTO - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.Clause

Value of the type variable.

subjecttoClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Counts the number of subjectto clauses for error detection.

subscript - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SubscriptVariable

(¬ø) The expression whose evaluation will be used as the subscript.

SubscriptVariable - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents an array access.

SubscriptVariable(Expression, Expression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SubscriptVariable

Initializing constructor.

subtract(PropositionalConstraint[]) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Subtraction from a conjunction simply removes all of the specified terms from it; this method returns a new constraint representing the subtraction.

subtract(PropositionalConstraint[]) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Subtraction from a disjunction simply removes all of the specified terms from it; this method returns a new constraint representing the subtraction.

sumAlphas(int[], double[]) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Computes the scores corresponding to the two prediction values for the given example.

sumOfSquareOfGoldSubtractPrediction - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.TestReal

SUPER - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

SupportVectorMachine - Class in edu.illinois.cs.cogcomp.lbjava.learn

Wrapper class for the liblinear library which supports support vector machine classification.

SupportVectorMachine() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Default constructor.

SupportVectorMachine(double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine(double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine(double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine(double, double, double, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine(double, double, double, String, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine(String, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine(String, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine(String, double, double, double) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine(String, double, double, double, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine(String, double, double, double, String, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine(SupportVectorMachine.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine(String, SupportVectorMachine.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Initializing constructor.

SupportVectorMachine.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

A container for all of SupportVectorMachine's configurable parameters.

SWITCH - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

SwitchBlock - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents the body of a switch statement.

SwitchBlock(int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

Initializing constructor.

SwitchBlock(SwitchLabelList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

Initializing constructor.

SwitchBlock(SwitchGroupList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

Initializing constructor.

SwitchBlock(SwitchGroupList, SwitchLabelList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

Initializing constructor.

SwitchBlock(SwitchGroupList, SwitchLabelList, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

Full constructor.

SwitchGroup - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a list of statements labeled by one or more SwitchLabels.

SwitchGroup(SwitchLabelList, StatementList) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroup

Full constructor.

SwitchGroupList - Class in edu.illinois.cs.cogcomp.lbjava.IR

Currently, this is just a wrapper class for LinkedList.

SwitchGroupList() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroupList

Default constructor.

SwitchGroupList(SwitchGroup) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroupList

Initializing constructor.

SwitchGroupList.SwitchGroupListIterator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Used to iterate though the children of a list of AST nodes.

SwitchGroupListIterator() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroupList.SwitchGroupListIterator

SwitchLabel - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a case or default label inside a switch block.

SwitchLabel(Expression, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabel

Full constructor.

SwitchLabelList - Class in edu.illinois.cs.cogcomp.lbjava.IR

Currently, this is just a wrapper class for LinkedList.

SwitchLabelList() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabelList

Default constructor.

SwitchLabelList(SwitchLabel) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabelList

Initializing constructor.

SwitchLabelList.SwitchLabelListIterator - Class in edu.illinois.cs.cogcomp.lbjava.IR

Used to iterate though the children of a list of AST nodes.

SwitchLabelListIterator() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabelList.SwitchLabelListIterator

SwitchStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a switch statement.

SwitchStatement(Expression, SwitchBlock, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SwitchStatement

Full constructor.

sym - Class in edu.illinois.cs.cogcomp.lbjava.frontend

CUP generated class containing symbol constants.

sym() - Constructor for class edu.illinois.cs.cogcomp.lbjava.frontend.sym

SymbolNames - Class in edu.illinois.cs.cogcomp.lbjava.frontend

SymbolNames() - Constructor for class edu.illinois.cs.cogcomp.lbjava.frontend.SymbolNames

symbolTable - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNode

The table of variable types representing this node's scope.

SymbolTable - Class in edu.illinois.cs.cogcomp.lbjava.IR

A symbol table is simply a HashMap associating names with their types.

SymbolTable() - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Initializes the member variables.

SymbolTable(SymbolTable) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SymbolTable

Initializes the member variables.

SYNCHRONIZED - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

SynchronizedStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a synchronized statement.

SynchronizedStatement(Expression, Block, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.SynchronizedStatement

Full constructor.

syntax_error(Symbol) - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

T

TableFormat - Class in edu.illinois.cs.cogcomp.lbjava.util

A library of routines for taking tabular data and producing a human readable string representation of it.

TableFormat() - Constructor for class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

tableFormat(double[][]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table.

tableFormat(Double[][]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table.

tableFormat(String[], String[], double[][]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table.

tableFormat(String[], String[], Double[][]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table.

tableFormat(String[], String[], double[][], int[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table.

tableFormat(String[], String[], Double[][], int[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table.

tableFormat(String[], String[], double[][], int[], int[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table.

tableFormat(String[], String[], Double[][], int[], int[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Formats the given data into an ASCII table.

tautology - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

This flag is set if the constraints turn out to be true in all cases.

test(Classifier, Classifier, Object[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Measures the performance of a classifier as compared with the values produced by an oracle.

test(Classifier, Classifier, Parser) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Accuracy

Evaluates a classifier against an oracle on the data provided by a parser.

test(Classifier, Classifier, Parser) - Method in interface edu.illinois.cs.cogcomp.lbjava.learn.TestingMetric

Evaluates a classifier against an oracle on the data provided by a parser.

TestDiscrete - Class in edu.illinois.cs.cogcomp.lbjava.classify

This class is a program that can evaluate any Classifier against an oracle Classifier on the objects returned from a Parser.

TestDiscrete() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Default constructor.

testDiscrete(Classifier, Classifier, Parser) - Static method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Tests the given discrete classifier against the given oracle using the given parser to provide the labeled testing data.

testDiscrete(TestDiscrete, Classifier, Classifier, Parser, boolean, int) - Static method in class edu.illinois.cs.cogcomp.lbjava.classify.TestDiscrete

Tests the given discrete classifier against the given oracle using the given parser to provide the labeled testing data.

testExFilePath - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

The file into which testing examples are extracted.

TESTFROM - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

TESTFROM - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Value of the type variable.

testFromClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Counts the number of testFrom clauses for error detection.

TESTINGMETRIC - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

TESTINGMETRIC - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Value of the type variable

testingMetric - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) Determines how the user wishes cross-validation to test its performance; argument to testingMetric.

TestingMetric - Interface in edu.illinois.cs.cogcomp.lbjava.learn

TestingMetric is an interface through which the user may implement their own testing method for use by LBJava's internal cross validation algorithm.

testingMetric - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

The metric with which to measure the learner's performance on a test set.

testingMetricClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Counts the number of testingMetric clauses, for error detection.

testMidTraining(Parser, TestingMetric, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Tests BatchTrainer.learner on the specified data while making provisions under the assumption that this test happens in between rounds of training.

testParser - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

(ø) Tells this learning classifier how to get its testing data; argument to testFrom.

testParser - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

The parser from which testing objects are obtained.

TestReal - Class in edu.illinois.cs.cogcomp.lbjava.classify

This class is a program that can evaluate any Classifier against an oracle Classifier on the objects returned from a Parser, with different statistical metrics.

TestReal() - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.TestReal

testReal(TestReal, Classifier, Classifier, Parser, boolean, int) - Static method in class edu.illinois.cs.cogcomp.lbjava.classify.TestReal

Tests the given real classifier against the given oracle using the given Parser to provide the real labeled testing data.

text - Variable in class edu.illinois.cs.cogcomp.lbjava.frontend.TokenValue

The text in the source file that comprises the token.

thenClause - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Conditional

(¬ø) The expression to evaluate if the condition evaluates to true.

thenClause - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.IfStatement

(¬ø) The statement to execute if the condition is true.

thickness - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit.Parameters

This thickness will be added to both LinearThresholdUnit.Parameters.positiveThickness and LinearThresholdUnit.Parameters.negativeThickness; default LinearThresholdUnit.defaultThickness.

THIS - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

threadMap - Variable in class edu.illinois.cs.cogcomp.lbjava.Train

A map of all the training threads indexed by the name of the learner.

threads - Variable in class edu.illinois.cs.cogcomp.lbjava.Train

An array of the training threads, which is never modified after it is constructed.

threshold - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit.Parameters

The score is compared against this value to make predictions; default LinearThresholdUnit.defaultThreshold.

threshold - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

The score is compared against this value to make predictions; default LinearThresholdUnit.defaultThreshold.

THROW - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

THROWS - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

ThrowStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a throw statement.

ThrowStatement(Expression, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.ThrowStatement

Full constructor.

TIMES - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

TIMES - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ScoreSet

Returns an array view of the Scores contained in this set.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Block

Transforms the list into an array of statements.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchList

Transforms the list into an array of statements.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierExpressionList

Transforms the list into an array of expressions.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstantList

Transforms the list into an array of expressions.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DeclarationList

Transforms the list into an array of statements.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionList

Transforms the list into an array of expressions.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportList

Transforms the list into an array of statements.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NameList

Transforms the list into an array of expressions.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.StatementList

Transforms the list into an array of statements.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroupList

Transforms the list into an array of statements.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabelList

Transforms the list into an array of statements.

toArray() - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Returns a new array of features containing the same data as this vector.

toBoolean() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.TokenValue

Attempts to parse the token's text as if it represented a boolean value.

toChar() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.TokenValue

Attempts to parse the token's text as if it represented a character value.

toDouble() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.TokenValue

Attempts to parse the token's text as if it represented a double precision floating point value.

toFloat() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.TokenValue

Attempts to parse the token's text as if it represented a double precision floating point value.

toInt() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.TokenValue

Attempts to parse the token's text as if it represented an integer.

TokenValue - Class in edu.illinois.cs.cogcomp.lbjava.frontend

Objects of this class are returned by LBJava's scanner to its parser.

TOLERANCE - Static variable in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Used to mitigate floating point error in (in)equality comparisons.

TOLERANCE - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Used to decide if two values are nearly equal to each other.

TOLERANCE - Static variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Used to decide if two values are nearly equal to each other.

toLong() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.TokenValue

Attempts to parse the token's text as if it represented an integer.

topLevel - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Used during ILP constraint generation.

toSortedIntArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Parses integers out of every constant in the set and returns them in a sorted array.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Simply returns the name of the classifier.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Returns a string representation of this Feature.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns the string representation of this FeatureVector as created by FeatureVector.write(StringBuffer).

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVectorReturner

Simply returns the string "FeatureVectorReturner".

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.LabelVectorReturner

Simply returns the string "LabelVectorReturner".

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.MultiValueComparer

The String representation of a ValueComparer has the form "ValueComparer(child), where child is the String representation of the classifier whose value is being compared.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Score

The string representation of a Score is the value followed by the score separated by a colon.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ScoreSet

The string representation of a ScoreSet is the concatenation of the string representations of each Score in the set sorted by value, separated by commas, and surrounded by curly braces.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ValueComparer

The String representation of a ValueComparer has the form "ValueComparer(child), where child is the String representation of the classifier whose value is being compared.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.frontend.TokenValue

Return the token's text in a String.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderVariable

Returns a string representation of this variable.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Creates a string respresentation of this constraint using the string representations of the objects involved.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Returns the representation created by ZeroOneILPProblem.write(StringBuffer).

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNode

Calls the write(StringBuffer) method to produce a string representation of this node.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.Clause

Debugging utility method.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Debugging utility method.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.CountPolicy

Retrieves the name of the policy represented by this object.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon.PruningPolicy

Retrieves the name of the policy represented by this object.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Returns a text representation of this lexicon (for debugging).

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Count

The string representation of a Count object is simply the integer count.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Creates a string representation of this SparseWeightVector.

toString(Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Creates a string representation of this SparseWeightVector.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser.SplitPolicy

Retrieves the name of the policy represented by this object.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Returns a decoded string.

toString() - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Returns a text representation of this vector.

toStringArray() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Assuming that ParameterSet.convertRange() has already been called (if necessary) and that every expression in ParameterSet.parameterList is a Constant, this method produces an array of Strings containing the values of the constants.

toStringJustWeights(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Outputs a textual representation of this SparseWeightVector to a stream just like SparseWeightVector.write(PrintStream), but without the "Begin" and "End" annotations.

toStringJustWeights(PrintStream, int, Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Outputs a textual representation of this SparseWeightVector to a stream just like SparseWeightVector.write(PrintStream), but without the "Begin" and "End" annotations.

toStringNoPackage() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Returns a string representation of this Feature omitting the package.

toStringNoPackage() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Returns the string representation of this FeatureVector like FeatureVector.toString() except without package names.

totalValues - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

The total number of allowable values for this feature.

totalValues() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

Returns the total number of values this feature might possibly be set to.

totalValues() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Returns the total number of values this feature might possibly be set to.

train(int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Trains BatchTrainer.learner for the specified number of rounds.

train(int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Trains BatchTrainer.learner for the specified number of rounds.

train(int, BatchTrainer.DoneWithRound) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Trains BatchTrainer.learner for the specified number of rounds.

train(int, int, BatchTrainer.DoneWithRound) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Trains BatchTrainer.learner for the specified number of rounds.

Train - Class in edu.illinois.cs.cogcomp.lbjava

After code has been generated with TranslateToJava, this pass trains any classifiers for which training was indicated.

Train(AST, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.Train

Instantiates a pass that runs on an entire AST.

Train.TrainingThread - Class in edu.illinois.cs.cogcomp.lbjava

This class contains the code that trains a learning classifier.

trained - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Indicates whether the WekaWrapper.doneLearning() method has been called and the WekaWrapper.forget() method has not yet been called.

trainer - Variable in class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

Actually does the training.

TrainingThread(String, int, LearningClassifierExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.Train.TrainingThread

Initializing constructor.

TRANSIENT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

TranslateToJava - Class in edu.illinois.cs.cogcomp.lbjava

This pass generates Java code from an AST, but does not perform any training.

TranslateToJava(AST) - Constructor for class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Associates an AST with this pass.

transpose(double[][]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Transposes the given matrix so that the rows become the columns and the columns become the rows.

transpose(Double[][]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Transposes the given matrix so that the rows become the columns and the columns become the rows.

True - Static variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

true

TRY - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

TryStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a try statement.

TryStatement(Block, CatchList, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.TryStatement

Initializing constructor.

TryStatement(Block, Block, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.TryStatement

Initializing constructor.

TryStatement(Block, CatchList, Block, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.TryStatement

Full constructor.

tTable(int, double) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.StudentT

Computes the multiplier for the standard error of the mean when finding a (1 - alpha) * 100% confidence interval.

tune(Learner.Parameters[], int[], int, FoldParser.SplitPolicy, double, TestingMetric) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Tune learning algorithm parameters using cross validation.

tune(Learner.Parameters[], int[], Parser, TestingMetric) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Tune learning algorithm parameters against a development set.

type - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayType

(¬ø) Represents the type of each element in the array.

type - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.CastExpression

(¬ø) The type to cast to.

type - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

The index of the type represented by this ClassifierReturnType.

type - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.Clause

The type of the clause.

type - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

The type of the clause.

type - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

The most specific type for the values in this set.

type - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

(¬ø) The index of the type represented by this PrimitiveType.

Type - Class in edu.illinois.cs.cogcomp.lbjava.IR

Abstract class representing the type of a variable or the return type of a method.

Type(int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.Type

Default constructor.

type - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

(¬ø) The type of the declared variable.

typeCache - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Expression

The SemanticAnalysis pass will store the type of this expression here.

typeCacheFilled - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Expression

Indicates whether the typeCache variable contains usable information.

typeCheckClassifyArray(PrintStream, String, Type, int) - Static method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Generates code that overrides the Classifier.classify(Object[]) method so that it checks the types of its arguments.

typeClass() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayType

Returns an object representing the class that this type represents.

typeClass() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Returns an object representing the class that this type represents.

typeClass() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Returns an object representing the class that this type represents.

typeClass() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReferenceType

Returns an object representing the class that this type represents.

typeClass() - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Type

Returns an object representing the class that this type represents.

typeName(int) - Static method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Produces the name of the primitive type given its index.

typeName(int) - Static method in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Produces the name of the primitive type given its index.

typeNames - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.Clause

String representations of the type names.

typeNames - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

String representations of the type names.

typeReturningMethods(PrintStream, Type, ClassifierReturnType) - Static method in class edu.illinois.cs.cogcomp.lbjava.TranslateToJava

Generate code that overrides the methods of Classifier that return type information.

U

UNAFFECTED - Static variable in class edu.illinois.cs.cogcomp.lbjava.RevisionAnalysis

Constant representing the "unaffected" revision status.

UnaryExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

This class represents an expression involving a unary operator.

UnaryExpression(Operator, Expression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.UnaryExpression

Initializing constructor.

unclone() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Automatically generated code will override this method to set their isClone field to false.

UniversalQuantifier - Class in edu.illinois.cs.cogcomp.lbjava.infer

A universal quantifier states that the constraint must hold for all objects from the collection.

UniversalQuantifier(String, Collection, FirstOrderConstraint) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.UniversalQuantifier

Initializing constructor.

UniversalQuantifier(String, Collection, FirstOrderConstraint, QuantifierArgumentReplacer) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.UniversalQuantifier

This constructor specifies a variable setter for when this quantifier is itself quantified.

UniversalQuantifierExpression - Class in edu.illinois.cs.cogcomp.lbjava.IR

A universal quantifier has the form: forall argument in (expression) constraint-expression where expression must evaluate to a Collection, and the universal quantifier expression is sastisfied iff constraint-expression is satisfied for all settings of argument taken from the Collection .

UniversalQuantifierExpression(int, int, Argument, Expression, ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.UniversalQuantifierExpression

Full constructor.

UniversalQuantifierExpression(TokenValue, Argument, Expression, ConstraintExpression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.UniversalQuantifierExpression

Parser's constructor.

unsetLossFlag() - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

UNSIGNED_RIGHT_SHIFT - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

UNSIGNED_RIGHT_SHIFT_ASSIGN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

update(int[], double[], double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

This method performs an update w_i *= basex_i, initalizing weights in the weight vector as needed.

updateAveragedWeight(int, double) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Adds a new value to the current averaged weight indexed by the supplied feature index.

updateLog - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Count

A flag that is set iff NaiveBayes.Count.logCount is not up to date.

updaters - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

(ø) The updating expression(s) in the loop header.

upperBound - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.AtMostQuantifierExpression

(¬ø) This expression evaluates to an integer representing the maximum number of objects that must satisfy the child constraint expression in order for this quantified constraint expression to be satisfied.

upperBound - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.FoldParser

An upper bound for an index relating to the pivot fold.

upperBoundIsQuantified - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.AtMostQuantifierExpression

Filled in by SemanticAnalysis, this flag is set if upperBound contains any quantified variables.

URSHIFT - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

URSHIFTEQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

USING - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

USING - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Value of the type variable.

usingClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Counts the number of using clauses for error detection.

V

value - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

The discrete value is represented as a string.

value - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

The discrete value is represented as a string.

value - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

The real value is represented as a double.

value - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

The real value is represented as a double.

value - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.Score

The discrete classification associated with this score.

value - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.ValueComparer

The value to compare with.

value - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

The value imposed on this variable.

value - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.Constant

(¬ø) The text representing the constant.

value - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

(¬ø) Represents the value of the feature being sensed.

value - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabel

(ø) The expression representing the value to match, if any.

value - Variable in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

The encoded characters.

ValueComparer - Class in edu.illinois.cs.cogcomp.lbjava.classify

This classifier applies another classifier to the example object and returns a Boolean feature (with value "true" or "false") representing the equality of the argument classifier's feature value to a given value.

ValueComparer(Classifier, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.classify.ValueComparer

Constructor.

valueEquals(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Determines whether or not the parameter is equivalent to the string representation of the value of this feature.

valueEquals(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Determines whether or not the parameter is equivalent to the string representation of the value of this feature.

valueEquals(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Determines whether or not the parameter is equivalent to the string representation of the value of this feature.

valueEquals(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Determines whether or not the parameter is equivalent to the string representation of the value of this feature.

valueEquals(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Determines whether or not the parameter is equivalent to the string representation of the value of this feature.

valueEquals(FeatureVector) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Two FeatureVectors have equal value if they contain the same number of Features and if the values of those Features are pair-wise equivalent according to the Feature.valueEquals(String) method.

valueEquals(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealFeature

Determines whether or not the parameter is equivalent to the string representation of the value of this feature.

valueIndex - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

Index into the set of allowable values corresponding to this value.

valueIndexOf(String) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Classifier

Locates the specified discrete feature value in the array of allowable values defined for this classifier.

valueOf(Learner, Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Retrieves the value of the specified variable as identified by the classifier and the object that produce that variable.

valueOf(Learner, Object) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Retrieves the value of the specified variable as identified by the classifier and the object that produce that variable.

valueOf(Object, Collection) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Using this method, the winner-take-all competition is narrowed to involve only those labels contained in the specified list.

valueOf(int[], double[], Collection) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Using this method, the winner-take-all competition is narrowed to involve only those labels contained in the specified list.

valueOf(Object, Collection) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Using this method, the winner-take-all competition is narrowed to involve only those labels contained in the specified list.

valueOf(int[], double[], Collection) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Using this method, the winner-take-all competition is narrowed to involve only those labels contained in the specified list.

valueOf(Object, Collection) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Using this method, the winner-take-all competition is narrowed to involve only those labels contained in the specified list.

valueOf(int[], double[], Collection) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Using this method, the winner-take-all competition is narrowed to involve only those labels contained in the specified list.

values() - Method in class edu.illinois.cs.cogcomp.lbjava.classify.ScoreSet

Retrieves the set of values that have scores associated with them in this score set.

values - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayInitializer

(¬ø) The list of expressions that represent the values in the array.

values - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

(¬ø) If the type is DISCRETE, this variable represents a list of legal values.

VariableDeclaration - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a local variable declaration.

VariableDeclaration(Name) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

Parser's constructor, leaving the type to be filled in later.

VariableDeclaration(Name, Expression) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

Parser's constructor, leaving the type to be filled in later.

VariableDeclaration(Type, NameList, ExpressionList, boolean) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

Full constructor.

VariableInstance - Class in edu.illinois.cs.cogcomp.lbjava.IR

Abstract class representing either a scalar or a subscript variable.

variableMap - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.FirstOrderEquality

The map that this constraint's variables have been consolidated into, or null if variable consolidation has not been performed.

variables - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

The values of this map are the variables we perform inference over; they are the actual FirstOrderVariable objects found in this inference's constraints.

variances - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted.Parameters

The current variances of the parameters; default LinearThresholdUnit.defaultWeightVector.

variances - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

The inverses of the current variances of the parameters.

variancesBias - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

The bias element of the SparseConfidenceWeighted.variances vector.

vector - Variable in class edu.illinois.cs.cogcomp.lbjava.util.FVector

The elements of the vector.

verbosity - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Verbosity level.

verbosity - Variable in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Verbosity level.

VERBOSITY_HIGH - Static variable in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

A possible setting for ILPInference.verbosity.

VERBOSITY_LOW - Static variable in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

A possible setting for ILPInference.verbosity.

VERBOSITY_NONE - Static variable in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

A possible setting for ILPInference.verbosity.

visit(PropositionalDoubleImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalAtLeast) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalNegation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalConstant) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ILPInference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(FirstOrderDoubleImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(FirstOrderImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(FirstOrderConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(FirstOrderDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(FirstOrderEqualityTwoValues) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(FirstOrderEqualityWithValue) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(FirstOrderEqualityWithVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(FirstOrderNegation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(FirstOrderConstant) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(UniversalQuantifier) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(ExistentialQuantifier) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(AtLeastQuantifier) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(AtMostQuantifier) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(QuantifiedConstraintInvocation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalDoubleImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalImplication) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalConjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalDisjunction) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalAtLeast) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalConstant) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalNegation) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visit(PropositionalVariable) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

Derived classes override this method to do some type of processing on constraints of the parameter's type.

visitAll(Constraint) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.Inference

The default method for visiting a constraint simply visits that constraint's children.

VOID - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

VOLATILE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

W

warningsDisabled - Static variable in class edu.illinois.cs.cogcomp.lbjava.Main

This flag is set if warnings have been disabled on the command line.

weakLearner - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost.Parameters

The weak learning algorithm to be boosted.

weakLearner - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

The weak learning algorithm to be boosted.

weakLearners - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Will be filled with trained copies of the weak learner.

weight - Variable in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

With this variable, the user can weight the entire vector.

weights - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

The weights in the vector indexed by their Lexicon key.

weights - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

An array of weights representing the weight vector learned after training with liblinear.

weightVector - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit.Parameters

The LTU's weight vector; default is an empty vector.

weightVector - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

The LTU's weight vector; default is an empty vector.

weightVector - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent.Parameters

The hypothesis vector; default StochasticGradientDescent.defaultWeightVector.

weightVector - Variable in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

The hypothesis vector; default StochasticGradientDescent.defaultWeightVector.

wekaIze(int, ClassifierReturnType, Name) - Method in class edu.illinois.cs.cogcomp.lbjava.SemanticAnalysis

Called when analyzing the feature types for use by a WEKA classifier.

WekaWrapper - Class in edu.illinois.cs.cogcomp.lbjava.learn

Translates LBJava's internal problem representation into that which can be handled by WEKA learning algorithms.

WekaWrapper() - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Empty constructor.

WekaWrapper(Classifier) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Partial constructor; attribute information must be provided before any learning can occur.

WekaWrapper(Classifier, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Redirecting constructor.

WekaWrapper(WekaWrapper.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Initializing constructor.

WekaWrapper(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Empty constructor.

WekaWrapper(String, Classifier) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Partial constructor; attribute information must be provided before any learning can occur.

WekaWrapper(String, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Default Constructor.

WekaWrapper(String, WekaWrapper.Parameters) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Initializing constructor.

WekaWrapper(String, Classifier, String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Full Constructor.

WekaWrapper.Parameters - Class in edu.illinois.cs.cogcomp.lbjava.learn

Simply a container for all of WekaWrapper's configurable parameters.

WHILE - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

WhileStatement - Class in edu.illinois.cs.cogcomp.lbjava.IR

Represents a while loop.

WhileStatement(Expression, Statement, int, int) - Constructor for class edu.illinois.cs.cogcomp.lbjava.IR.WhileStatement

Full constructor.

WITH - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

WITH - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.Clause

Value of the type variable.

WITH - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression.Clause

Value of the type variable.

withClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Counts the number of with clauses for error detection.

withClauses - Variable in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Counts the number of with clauses for error detection.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

withStrength(double) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Returns a new feature object that's identical to this feature except its strength is given by s.

wrapDouble(double[][]) - Static method in class edu.illinois.cs.cogcomp.lbjava.util.TableFormat

Simply converts the type of the given matrix from double to Double.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayFeature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteArrayStringFeature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Writes a complete binary representation of the feature.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteFeature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Writes a complete binary representation of the feature.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Writes a complete binary representation of the feature.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Creates a string representation of this FeatureVector.

write(StringBuffer, boolean) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Creates a string representation of this FeatureVector.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.FeatureVector

Writes a binary representation of the feature vector.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayFeature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealArrayStringFeature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Writes a string representation of this Feature to the specified buffer.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Writes a complete binary representation of the feature.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Writes a complete binary representation of the feature.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Writes a complete binary representation of the feature.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.BalasHook

Creates a textual representation of the ILP problem in an algebraic notation.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalAtLeast

Creates a string respresentation of this constraint using the string representations of the objects involved.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConjunction

Creates a string respresentation of this constraint using the string representations of the objects involved.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstant

Creates a string respresentation of this constraint using the string representations of the objects involved.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalConstraint

Creates a string respresentation of this constraint using the string representations of the objects involved.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDisjunction

Creates a string respresentation of this constraint using the string representations of the objects involved.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalDoubleImplication

Creates a string respresentation of this constraint using the string representations of the objects involved.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalImplication

Creates a string respresentation of this constraint using the string representations of the objects involved.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalNegation

Creates a string respresentation of this constraint using the string representations of the objects involved.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.PropositionalVariable

Creates a string respresentation of this constraint using the string representations of the objects involved.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Creates a textual representation of the ILP problem in an algebraic notation.

write(int) - Method in class edu.illinois.cs.cogcomp.lbjava.io.ChannelOutputStream

Writes the specified byte to this channel output stream.

write(byte[], int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.io.ChannelOutputStream

Writes len bytes from the specified byte array starting at offset off to this channel output stream.

write(int) - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexOutputStream

Writes the specified byte to this output stream.

write(byte[]) - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexOutputStream

Writes b.length bytes from the specified byte array to this output stream.

write(byte[], int, int) - Method in class edu.illinois.cs.cogcomp.lbjava.io.HexOutputStream

Writes len bytes from the specified byte array starting at offset off to this output stream.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Argument

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayCreationExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayInitializer

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ArrayType

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AssertStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Assignment

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AST

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ASTNode

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AtLeastQuantifierExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.AtMostQuantifierExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryConstraintExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BinaryExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Block

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.BreakStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CastExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CatchClause

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierAssignment

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierCastExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierName

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierReturnType

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ClassifierType

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CodedClassifier

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.CompositeGenerator

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conditional

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Conjunction

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Constant

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintDeclaration

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintEqualityExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintInvocation

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintStatementExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ConstraintType

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ContinueStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.DoStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.EmptyStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExistentialQuantifierExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ExpressionStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.FieldAccess

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ForStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.IfStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ImportDeclaration

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.IncrementExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.HeadFinder

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration.NormalizerDeclaration

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceDeclaration

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceInvocation

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InferenceType

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InstanceCreationExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.InstanceofExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LabeledStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.LearningClassifierExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.MethodInvocation

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Name

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NegatedConstraintExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.NormalizerType

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PackageDeclaration

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ParameterSet

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.PrimitiveType

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReferenceType

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ReturnStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SenseStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SubscriptVariable

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchBlock

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchGroup

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchLabel

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SwitchStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.SynchronizedStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.ThrowStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.TryStatement

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.UnaryExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.UniversalQuantifierExpression

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.VariableDeclaration

Writes a string representation of this ASTNode to the specified buffer.

write(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.WhileStatement

Writes a string representation of this ASTNode to the specified buffer.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Writes this algorithm's internal representation as text.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaBoost

Writes the learned function's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.AdaGrad

Writes the learned function's internal representation as text.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedRandomWeightVector

Outputs a textual representation of this vector to the specified stream.

write(PrintStream, Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedRandomWeightVector

Outputs a textual representation of this vector to the specified stream.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedRandomWeightVector

Writes the weight vector's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

Outputs the contents of this BiasedWeightVector into the specified PrintStream.

write(PrintStream, Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

Outputs the contents of this BiasedWeightVector into the specified PrintStream.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BiasedWeightVector

Writes the weight vector's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Writes the algorithm's internal representation as text.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.BinaryMIRA

Writes the learned function's internal representation in binary form.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.ChildLexicon

Writes a binary representation of the lexicon.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Writes the learned function's internal representation as text.

write(String, String) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Writes the learned function's binary internal represetation including both its model and lexicons to the specified files.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Writes the learned function's internal representation in binary form.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Lexicon

Writes a binary representation of the lexicon.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Writes the learned function's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Writes the algorithm's internal representation as text.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.MuxLearner

Writes the learned function's internal representation in binary form.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.Count

Writes the count's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Outputs the contents of this vector into the specified PrintStream.

write(PrintStream, Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Outputs the contents of this vector into the specified PrintStream.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes.NaiveBayesVector

Writes the weight vector's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Writes the algorithm's internal representation as text.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.NaiveBayes

Writes the learned function's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.PassiveAggressive

Writes the algorithm's internal representation as text.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

Outputs the contents of this vector into the specified PrintStream.

write(PrintStream, Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

Outputs the contents of this vector into the specified PrintStream.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.RandomWeightVector

Writes the weight vector's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Outputs the contents of this SparseWeightVector into the specified PrintStream.

write(PrintStream, Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Outputs the contents of this SparseWeightVector into the specified PrintStream.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron.AveragedWeightVector

Writes the weight vector's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Writes the algorithm's internal representation as text.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseAveragedPerceptron

Writes the learned function's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Writes the algorithm's internal representation as text.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseConfidenceWeighted

Writes the learned function's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Writes the algorithm's internal representation as text.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseMIRA

Writes the learned function's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Writes the algorithm's internal representation as text.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner

Writes the learned function's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparsePerceptron

Writes the algorithm's internal representation as text.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Outputs the contents of this SparseWeightVector into the specified PrintStream.

write(PrintStream, Lexicon) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Outputs the contents of this SparseWeightVector into the specified PrintStream.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWeightVector

Writes the weight vector's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Writes the algorithm's internal representation as text.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SparseWinnow

Writes the learned function's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Writes the algorithm's internal representation as text.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.StochasticGradientDescent

Writes the learned function's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Writes the algorithm's internal representation as text.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.SupportVectorMachine

Writes the learned function's internal representation in binary form.

write(PrintStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Writes the settings of the classifier in use, and a string describing the classifier, if available.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.WekaWrapper

Writes the learned function's internal representation in binary form.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.util.ByteString

Writes a complete binary representation of this byte string.

write(ExceptionlessOutputStream) - Method in class edu.illinois.cs.cogcomp.lbjava.util.FVector

Writes a binary representation of this vector to the given stream.

writeBuffer(StringBuffer, String) - Method in class edu.illinois.cs.cogcomp.lbjava.IR.List

Writes a string representation of this ASTNode to the specified buffer.

writeExample(ExceptionlessOutputStream, int[], double[], int[], double[]) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Writes an example vector to the specified stream, with all features being written in the order they appear in the vector.

writeExample(ExceptionlessOutputStream, int[], double[], int[], double[], int) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Writes an example vector to the specified stream, with all features being written in the order they appear in the vector.

writeExample(ExceptionlessOutputStream, int[], double[], int[], double[], Lexicon) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Writes an example vector contained in an object array to the underlying output stream, with features sorted according to their representations in the given lexicon if present, or in the order they appear in the vector otherwise.

writeExample(ExceptionlessOutputStream, int[], double[], int[], double[], int, Lexicon) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.BatchTrainer

Writes an example vector contained in an object array to the underlying output stream, with features sorted according to their representations in the given lexicon if present, or in the order they appear in the vector otherwise.

writeLexicon(String) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Writes the learned function's feature lexicon to the specified file.

writeModel(String) - Method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Writes only the learned function's model (which includes the label lexicon) to the specified file in binary form.

writeNameString(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveFeature

Writes a string representation of this Feature's package, generating classifier, and identifier information to the specified buffer.

writeNameString(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscretePrimitiveStringFeature

Writes a string representation of this Feature's package, generating classifier, and identifier information to the specified buffer.

writeNameString(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringFeature

Writes a string representation of this Feature's package, generating classifier, and identifier information to the specified buffer.

writeNameString(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferringStringFeature

Writes a string representation of this Feature's package, generating classifier, and identifier information to the specified buffer.

writeNameString(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Writes a string representation of this Feature's package, generating classifier, and sometimes identifier information to the specified buffer.

writeNameString(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveFeature

Writes a string representation of this Feature's package, generating classifier, and identifier information to the specified buffer.

writeNameString(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealPrimitiveStringFeature

Writes a string representation of this Feature's package, generating classifier, and identifier information to the specified buffer.

writeNameString(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringFeature

Writes a string representation of this Feature's package, generating classifier, and identifier information to the specified buffer.

writeNameString(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferringStringFeature

Writes a string representation of this Feature's package, generating classifier, and identifier information to the specified buffer.

writeNoPackage(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteConjunctiveFeature

Writes a string representation of this Feature to the specified buffer, omitting the package name.

writeNoPackage(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.DiscreteReferrer

Writes a string representation of this Feature to the specified buffer, omitting the package name.

writeNoPackage(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.Feature

Writes a string representation of this Feature to the specified buffer, omitting the package name.

writeNoPackage(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealConjunctiveFeature

Writes a string representation of this Feature to the specified buffer, omitting the package name.

writeNoPackage(StringBuffer) - Method in class edu.illinois.cs.cogcomp.lbjava.classify.RealReferrer

Writes a string representation of this Feature to the specified buffer, omitting the package name.

writeParameters(Learner.Parameters, String) - Static method in class edu.illinois.cs.cogcomp.lbjava.learn.Learner

Serializes a Learner.Parameters object to the specified file.

X

XOR - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

XOR - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

XOR_ASSIGN - Static variable in class edu.illinois.cs.cogcomp.lbjava.IR.Operator

Value of the operation variable.

XOREQ - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.sym

Y

Yylex - Class in edu.illinois.cs.cogcomp.lbjava.frontend

Yylex(Reader) - Constructor for class edu.illinois.cs.cogcomp.lbjava.frontend.Yylex

Yylex(InputStream) - Constructor for class edu.illinois.cs.cogcomp.lbjava.frontend.Yylex

Z

ZeroOneILPProblem - Class in edu.illinois.cs.cogcomp.lbjava.infer

Can be used to represent an ILP problem, assuming all variables are 0-1.

ZeroOneILPProblem() - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Default constructor.

ZeroOneILPProblem(String) - Constructor for class edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Reads a textual representation of a 0-1 ILP problem from the specified file.

zipped - Variable in class edu.illinois.cs.cogcomp.lbjava.parse.ArrayFileParser

Whether or not the input stream is zipped.

_

_action_table - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Parse-action table.

_production_table - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

Production table.

_reduce_table - Static variable in class edu.illinois.cs.cogcomp.lbjava.frontend.parser

reduce_goto table.

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z _