Package: naivebayes 1.0.0
naivebayes: High Performance Implementation of the Naive Bayes Algorithm
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.
Authors:
naivebayes_1.0.0.tar.gz
naivebayes_1.0.0.zip(r-4.5)naivebayes_1.0.0.zip(r-4.4)naivebayes_1.0.0.zip(r-4.3)
naivebayes_1.0.0.tgz(r-4.4-any)naivebayes_1.0.0.tgz(r-4.3-any)
naivebayes_1.0.0.tar.gz(r-4.5-noble)naivebayes_1.0.0.tar.gz(r-4.4-noble)
naivebayes_1.0.0.tgz(r-4.4-emscripten)naivebayes_1.0.0.tgz(r-4.3-emscripten)
naivebayes.pdf |naivebayes.html✨
naivebayes/json (API)
NEWS
# Install 'naivebayes' in R: |
install.packages('naivebayes', repos = c('https://majkamichal.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/majkamichal/naivebayes/issues
classification-modeldatasciencemachine-learningnaive-bayes
Last updated 8 months agofrom:02400ef5f7. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 15 2024 |
R-4.5-win | OK | Nov 15 2024 |
R-4.5-linux | OK | Nov 15 2024 |
R-4.4-win | OK | Nov 15 2024 |
R-4.4-mac | OK | Nov 15 2024 |
R-4.3-win | OK | Nov 15 2024 |
R-4.3-mac | OK | Nov 15 2024 |
Exports:%class%%prob%bernoulli_naive_bayesgaussian_naive_bayesget_cond_distmultinomial_naive_bayesnaive_bayesnonparametric_naive_bayespoisson_naive_bayestables
Dependencies: