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Bayes

Project description

Documentation Pypi

Bayes

Python implementations of Naive Bayes algorithm variations with sklearn-like API.

Algorithms

  • Complement Naive Bayes
  • Negation Naive Bayes
  • Universal-set Naive Bayes
  • Selective Naive Bayes

Installation

You can install this module directly from GitHub repo with command:

pip install git+https://github.com/krzjoa/Bayes.git

or using pip:

pip install bayes-variants

Usage

Bayes classifiers API mimics [Scikit-Learn](http://scikit-learn.org/stable/modules/classes.html) API, so usage is very simple.

from bayes.classifiers import ComplementNB
from sklearn.datasets import fetch_20newsgroups
from sklearn.feature_extraction.text import CountVectorizer


vectorizer = CountVectorizer()
categories = ['alt.atheism', 'talk.religion.misc',
              'comp.graphics', 'sci.space']

# Train set
newsgroups_train = fetch_20newsgroups(subset='train',
                                          categories=categories, shuffle=True)
X_train = vectorizer.fit_transform(newsgroups_train.data)
y_train = newsgroups_train.target

# Test set
newsgroups_test = fetch_20newsgroups(subset='test',
                                          categories=categories, 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)

TODO list

  • Weighted Complement Naive Bayes
  • Locally Weighted Naive Bayes

Documentation

The full documentation is at http://bayes.rtfd.org.

Project details


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