mskogholt/fastNaiveBayes: 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. 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) <doi:10.3115/1067807.1067848>. Any issues can be submitted to: <https://github.com/mskogholt/fastNaiveBayes/issues>.

Getting started

Package details

AuthorMartin Skogholt
MaintainerMartin Skogholt <m.skogholt@gmail.com>
LicenseGPL-3
Version2.2.1
URL https://github.com/mskogholt/fastNaiveBayes
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("mskogholt/fastNaiveBayes")
mskogholt/fastNaiveBayes documentation built on May 10, 2020, 6:09 p.m.