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 |
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