Train NLTK objects with zero code
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docs
nltk_trainer
tests
.hgignore
LICENSE
README.rst
analyze_chunked_corpus.py
analyze_chunker_coverage.py
analyze_classifier_coverage.py
analyze_tagged_corpus.py
analyze_tagger_coverage.py
categorized_corpus2csv.py
classify_corpus.py
combine_classifiers.py
requirements.txt
setup.py
tag_phrases.py
train_chunker.py
train_classifier.py
train_tagger.py
translate_corpus.py

README.rst

NLTK Trainer

NLTK Trainer exists to make training and evaluating NLTK objects as easy as possible.

Requirements

You must have Python >=2.6 (but not 3.x) with argparse and NLTK 2.0 installed. NumPy, SciPy, and megam are recommended for training Maxent classifiers. To use the sklearn classifiers, you must also install scikit-learn.

If you want to use any of the corpora that come with NLTK, you should install the NLTK data.

Documentation

Documentation can be found at nltk-trainer.readthedocs.org (you can also find these documents in the docs directory. Every script also provides a --help option that describes all available parameters.