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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 WooORCID iD [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.html ,bbl.pdf
Vignettes:bbl: Boltzmann Bayes Learner for High-Dimensional Inference with Discrete Predictors in R (source,R code)

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:

Please use the canonical formhttps://CRAN.R-project.org/package=bblto link to this page.


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