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RandomGaussianNB: Randomized Feature and Bootstrap-Enhanced Gaussian Naive Bayes Classifier

Provides an accessible and efficient implementation of a randomized feature and bootstrap-enhanced Gaussian naive Bayes classifier. The method combines stratified bootstrap resampling with random feature subsampling and aggregates predictions via posterior averaging. Support is provided for mixed-type predictors and parallel computation. Methods are described in Srisuradetchai (2025) <doi:10.3389/fdata.2025.1706417> "Posterior averaging with Gaussian naive Bayes and the R package RandomGaussianNB for big-data classification".

Version: 0.2.4
Imports: parallel, stats
Suggests: mlbench, testthat (≥ 3.0.0)
Published: 2026-01-07
DOI: 10.32614/CRAN.package.RandomGaussianNB
Author: Patchanok Srisuradetchai [aut, cre]
Maintainer: Patchanok Srisuradetchai <patchanok at mathstat.sci.tu.ac.th>
License: MIT + file LICENSE
NeedsCompilation: no
Citation: RandomGaussianNB citation info
Materials: README, NEWS
CRAN checks: RandomGaussianNB results

Documentation:

Reference manual: RandomGaussianNB.html , RandomGaussianNB.pdf

Downloads:

Package source: RandomGaussianNB_0.2.4.tar.gz
Windows binaries: r-devel: RandomGaussianNB_0.2.4.zip, r-release: RandomGaussianNB_0.2.4.zip, r-oldrel: RandomGaussianNB_0.2.4.zip
macOS binaries: r-release (arm64): RandomGaussianNB_0.2.4.tgz, r-oldrel (arm64): RandomGaussianNB_0.2.4.tgz, r-release (x86_64): RandomGaussianNB_0.2.4.tgz, r-oldrel (x86_64): RandomGaussianNB_0.2.4.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=RandomGaussianNB to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.