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. Woo et al. (2016) <doi:10.1186/s12864-016-2871-3>.

Version: 0.4.1
Depends: R (≥ 3.6.0)
Imports: methods, stats, utils, Rcpp (≥ 0.12.16), pROC, RColorBrewer
LinkingTo: Rcpp
Suggests: glmnet, BiocManager, Biostrings
Published: 2021-11-18
Author: Jun Woo ORCID iD [aut, cre]
Maintainer: Jun Woo <junwoo035 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README
CRAN checks: bbl results


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


Package source: bbl_0.4.1.tar.gz
Windows binaries: r-devel:, r-devel-UCRT:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): bbl_0.4.1.tgz, r-release (x86_64): bbl_0.4.1.tgz, r-oldrel: bbl_0.4.1.tgz
Old sources: bbl archive


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