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fastNaiveBayes
View on CRAN: Click
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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]
[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 07 Jun. 2026.
Previous versions and publish date:
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Complete documentation for fastNaiveBayes
Functions, R codes and Examples using
the fastNaiveBayes R package
Some associated functions: fastNaiveBayesF . fnb.detect_distribution . fnb.io . predict.fastNaiveBayes . tweets . tweetsDTM . updateFNB .
Some associated R codes: data.R . fastNaiveBayes.R . fnb.bernoulli.R . fnb.check.args.R . fnb.detect_distribution.R . fnb.gaussian.R . fnb.io.R . fnb.multinomial.R . fnb.poisson.R . fnb.train.R . fnb.update.R . fnb.utils.R . Full fastNaiveBayes package functions and examples
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