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) "Posterior averaging with Gaussian naive Bayes and the R package RandomGaussianNB for big-data classification".

RandomGaussianNB

An R package implementing the Random Gaussian Naive Bayes (RFB-NB) classifier: a bootstrap- and feature-randomized ensemble of Gaussian Naive Bayes models with posterior averaging.

The method is designed for high-dimensional classification, combining the simplicity of Naive Bayes with robustness from bootstrap aggregation and random subspace selection.

Installation

From source (local or CRAN-ready)

install.packages("RandomGaussianNB")