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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