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