bbl: Boltzmann Bayes Learner

Supervised learning using Boltzmann Bayes model inference, which extends naive Bayes model to include interactions. Enables classification of data into multiple response groups based on a large number of discrete predictors that can take factor values of heterogeneous levels. Either pseudo-likelihood or mean field inference can be used with L2 regularization, cross-validation, and prediction on new data. <doi:10.18637/jss.v101.i05>.

Version:	1.0.0
Depends:	R (≥ 3.6.0)
Imports:	methods, stats, utils, Rcpp (≥ 0.12.16), pROC, RColorBrewer
LinkingTo:	Rcpp
Suggests:	glmnet, BiocManager, Biostrings
Published:	2022-01-27
DOI:	10.32614/CRAN.package.bbl
Author:	Jun Woo [aut, cre]
Maintainer:	Jun Woo <junwoo035 at gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
Citation:	bbl citation info
Materials:	README
CRAN checks:	bbl results

Documentation:

Reference manual:	bbl.pdf
Vignettes:	bbl: Boltzmann Bayes Learner for High-Dimensional Inference with Discrete Predictors in R

Downloads:

Package source:	bbl_1.0.0.tar.gz
Windows binaries:	r-devel: bbl_1.0.0.zip, r-release: bbl_1.0.0.zip, r-oldrel: bbl_1.0.0.zip
macOS binaries:	r-release (arm64): bbl_1.0.0.tgz, r-oldrel (arm64): bbl_1.0.0.tgz, r-release (x86_64): bbl_1.0.0.tgz, r-oldrel (x86_64): bbl_1.0.0.tgz
Old sources:	bbl archive

Linking:

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