A deck of Naive Bayes algorithms with sklearn-like API.
- Complement Naive Bayes
- Negation Naive Bayes
- Universal-set Naive Bayes
- Selective Naive Bayes
You can install this module directly from GitHub repo with command:
python3.7 -m pip install git+https://github.com/krzjoa/bace.git
or as a PyPI package
python3.7 -m pip install bace
bace API mimics scikit-learn API, so usage is very simple.
from bace import ComplementNB from sklearn.datasets import fetch_20newsgroups from sklearn.feature_extraction.text import CountVectorizer vectorizer = CountVectorizer() # Train set newsgroups_train = fetch_20newsgroups(subset='train', shuffle=True) X_train = vectorizer.fit_transform(newsgroups_train.data) y_train = newsgroups_train.target # Test set newsgroups_test = fetch_20newsgroups(subset='test', shuffle=True) X_test = vectorizer.fit_transform(newsgroups_test.data) y_test = newsgroups_test.target # Score cnb = ComplementNB() cnb.fit(X_train, y_train).accuracy_score(X_test, y_test)
The full documentation is at http://bace.rtfd.org.
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