CRAN/E | naivebayes

naivebayes

High Performance Implementation of the Naive Bayes Algorithm

Installation

About

In this implementation of the Naive Bayes classifier following class conditional distributions are available: Bernoulli, Categorical, Gaussian, Poisson 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.

Citation naivebayes citation info
github.com/majkamichal/naivebayes
majkamichal.github.io/naivebayes/
Bug report File report

Key Metrics

Version 0.9.7
Published 2020-03-08 1368 days ago
Needs compilation? no
License GPL-2
CRAN checks naivebayes results

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Maintainer

Maintainer

Michal Majka

michalmajka@hotmail.com

Authors

Michal Majka

Material

NEWS
Reference manual
Package source

In Views

MachineLearning
MissingData

Vignettes

An Introduction to Naivebayes

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

naivebayes archive

Suggests

knitr
Matrix

Reverse Depends

fasi

Reverse Imports

MLFS
ModTools
npcs
nproc
PrInCE

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