In this implementation of the Naive Bayes classifier following class conditional distributions are available: 'Bernoulli', 'Categorical', 'Gaussian', 'Poisson', 'Multinomial' and non-parametric representation of the class conditional density estimated via Kernel Density Estimation. Implemented classifiers handle missing data and can take advantage of sparse data.
| Version: | 1.0.0 | 
| Suggests: | knitr, Matrix | 
| Published: | 2024-03-16 | 
| DOI: | 10.32614/CRAN.package.naivebayes | 
| Author: | Michal Majka | 
| Maintainer: | Michal Majka <michalmajka at hotmail.com> | 
| BugReports: | https://github.com/majkamichal/naivebayes/issues | 
| License: | GPL-2 | 
| URL: | https://github.com/majkamichal/naivebayes, https://majkamichal.github.io/naivebayes/ | 
| NeedsCompilation: | no | 
| Citation: | naivebayes citation info | 
| Materials: | NEWS | 
| In views: | MachineLearning, MissingData | 
| CRAN checks: | naivebayes results | 
| Reference manual: | naivebayes.html , naivebayes.pdf | 
| Vignettes: | An Introduction to Naivebayes (source, R code) | 
| Package source: | naivebayes_1.0.0.tar.gz | 
| Windows binaries: | r-devel: naivebayes_1.0.0.zip, r-release: naivebayes_1.0.0.zip, r-oldrel: naivebayes_1.0.0.zip | 
| macOS binaries: | r-release (arm64): naivebayes_1.0.0.tgz, r-oldrel (arm64): naivebayes_1.0.0.tgz, r-release (x86_64): naivebayes_1.0.0.tgz, r-oldrel (x86_64): naivebayes_1.0.0.tgz | 
| Old sources: | naivebayes archive | 
| Reverse imports: | AnimalSequences, MLFS, ModTools, nproc, PrInCE, promor | 
| Reverse suggests: | caretSDM, discrim, FRESA.CAD, quanteda.textmodels, StatMatch, superml | 
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