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fastNaiveBayes  

Extremely Fast Implementation of a Naive Bayes Classifier
View on CRAN: Click here


Download and install fastNaiveBayes package within the R console
Install from CRAN:
install.packages("fastNaiveBayes")

Install from Github:
library("remotes")
install_github("cran/fastNaiveBayes")

Install by package version:
library("remotes")
install_version("fastNaiveBayes", "2.2.1")



Attach the package and use:
library("fastNaiveBayes")
Maintained by
Martin Skogholt
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-02-28
Latest Update: 2020-05-04
Description:
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) . Any issues can be submitted to: .
How to cite:
Martin Skogholt (2019). fastNaiveBayes: Extremely Fast Implementation of a Naive Bayes Classifier. R package version 2.2.1, https://cran.r-project.org/web/packages/fastNaiveBayes. Accessed 06 Jan. 2025.
Previous versions and publish date:
1.0.0 (2019-02-28 12:20), 1.0.1 (2019-03-08 12:22), 1.1.1 (2019-03-31 19:10), 1.1.2 (2019-04-16 12:33), 2.1.0 (2019-08-28 07:30), 2.1.1 (2020-02-09 14:00), 2.2.0 (2020-02-23 16:10)
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