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 (may not be active yet)
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: not available
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:

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