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See:
Description
| Packages | |
|---|---|
| LBJ2.classify | Contains classes representing classifiers and features, as well as utility classes related to classifiers and features that may come in handy. |
| LBJ2.infer | Inference algorithms are implemented here (derived from
Inference), but most of the classes in this package are
used internally by LBJ at runtime to represent constraints and to translate
between constraint representations. |
| LBJ2.jni | Classes with methods implemented in C++ are kept in this package; currently
the only one is GLPKHook. |
| LBJ2.learn | Learning algorithms, normalizers (used in inference; see
Normalizer), testing metrics (used in cross validation; see
TestingMetric), and other utility classes can be found in
this package. |
| LBJ2.nlp | Parsers, data structures, pre-processing algorithms, and common feature extracting classifiers (implemented with LBJ) useful for natural language processing are implemented in this package. |
| LBJ2.nlp.seg | The segmentation of sequences of words into semantically meaningful groups is a common NLP paradigm; this package aims to support such tasks in a general way. |
| LBJ2.parse | Here, a couple of general purpose data structures and parsers that instantiate
them are defined, as well as the Parser interface, which is
central to the LBJ learning classifier syntax. |
| LBJ2.util | Utility routines for math related stuff, formatting, etc., are defined here. |
Contained in these packages are the base classes that all classifiers and constraints are derived from, implementations of learning and inference algorithms, general purpose and domain specific data structures, parsing algorithms for instantiating those data structures, and implementations of domain specific classifiers.
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