fastNaiveBayes (1.1.2)

0 users

Extremely Fast Implementation of a Naive Bayes Classifier.

This is an extremely fast implementation of a Naive Bayes classifier. This package is currently the only package that supports a Bernoulli distribution, a Multinomial distribution, and a Gaussian distribution, making it suitable for both binary features, frequency counts, and numerical features. Another feature is the support of a mix of different event models. Only numerical variables are allowed, however, categorical variables can be transformed into dummies and used with the Bernoulli distribution. This implementation offers a huge performance gain compared to other implementations in R. The execution times were compared on a data set of tweets and this package was found to be around 283 to 34,841 times faster for the Bernoulli event models and 17 to 60 times faster for the Multinomial model. See the vignette for more details. For the Gaussian distribution this package was found to be between 2.8 and 1679 times faster. The implementation is largely based on the paper "A comparison of event models for Naive Bayes anti-spam e-mail filtering" written by K.M. Schneider (2003) . Any issues can be submitted to: .

Maintainer: Martin Skogholt
Author(s): Martin Skogholt

License: GPL-3

Uses: Matrix, testthat, knitr, rmarkdown

Released 4 months ago.

3 previous versions



  (0 votes)


  (0 votes)

Log in to vote.


No one has written a review of fastNaiveBayes yet. Want to be the first? Write one now.

Related packages:(20 best matches, based on common tags.)

Search for fastNaiveBayes on google, google scholar, r-help, r-devel.

Visit fastNaiveBayes on R Graphical Manual.