Learning Discrete Bayesian Network Classifiers from Data R package bnclassify version 0.4.8 State-of-the art algorithms for learning discrete Bayesian network classifiers from data, including a number of those described in Bielza & Larranaga (2014) <doi:10.1145/2576868>, with functions for prediction, model evaluation and inspection. Software Depends: R (>= 3.2.0) Imports: assertthat (>= 0.1), entropy(>= 1.2.0), matrixStats(>= 0.14.0), rpart(>= 4.1-8), Rcpp, LinkingTo: Rcpp, BH Suggests: igraph, gRain(>= 1.2-3), gRbase(>= 1.7-0.1), mlr(>= 2.2), testthat(>= 0.8.1), knitr(>= 1.10.5), ParamHelpers(>= 1.5), rmarkdown(>= 0.7), mlbench, covr Mihaljevic Bojan <boki.mihaljevic@gmail.com> Comprehensive R Archive Network (CRAN) Mihaljevic Bojan [aut, cre, cph], Bielza Concha [aut], Larranaga Pedro [aut], Wickham Hadley [ctb] (some code extracted from memoise package) GPL (>= 2) 2024-03-13 application/tgz https://CRAN.R-project.org/package=bnclassify doi:10.32614/CRAN.package.bnclassify