Randomized Feature and Bootstrap-Enhanced Gaussian Naive Bayes Classifier
Overview
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".
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 2
- Examples that run
- no examples
- Exported functions with examples
- 0%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing RandomGaussianNB adds no packages beyond those that come with R.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- 0.2.4Latest2026-01-07 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-01-07
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 9.0 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("RandomGaussianNB")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.3389/fdata.2025.1706417.
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For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.