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Project description


Python 3.7 PyPI version Build Status Documentation Status License: MIT

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+

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(
y_train =

# Test set
newsgroups_test = fetch_20newsgroups(subset='test', shuffle=True)
X_test = vectorizer.fit_transform(
y_test =

# Score 
cnb = ComplementNB(), y_train).accuracy_score(X_test, y_test)


The full documentation is at

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