Package: fastNaiveBayes
Type: Package
Title: Extremely Fast Implementation of a Naive Bayes Classifier
Version: 1.1.2
Author: Martin Skogholt
Maintainer: Martin Skogholt <m.skogholt@gmail.com>
Description: This is an extremely fast implementation of a Naive Bayes classifier. This 
    package is currently the only package that supports a Bernoulli distribution, a Multinomial 
    distribution, and a Gaussian distribution, making it suitable for both binary features, 
    frequency counts, and numerical features. Another feature is the support of a mix of 
    different event models. Only numerical variables are allowed, however, categorical variables 
    can be transformed into dummies and used with the Bernoulli distribution. This implementation 
    offers a huge performance gain compared to other implementations in R. The execution times 
    were compared on a data set of tweets and this package was found to be around 283 to 34,841 
    times faster for the Bernoulli event models and 17 to 60 times faster for the Multinomial model. 
    See the vignette for more details. For the Gaussian distribution this package was found to be 
    between 2.8 and 1679 times faster. The implementation is largely based on the paper 
    "A comparison of event models for Naive Bayes anti-spam e-mail filtering" 
    written by K.M. Schneider (2003) <doi:10.3115/1067807>. Any issues can be 
    submitted to: <https://github.com/mskogholt/fastNaiveBayes/issues>.
Depends: R (>= 3.2.0)
License: GPL-3
Encoding: UTF-8
URL: https://github.com/mskogholt/fastNaiveBayes
BugReports: https://github.com/mskogholt/fastNaiveBayes/issues
LazyData: TRUE
Imports: Matrix, stats
Suggests: knitr, rmarkdown, testthat
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-16 10:11:59 UTC; Martin
Repository: CRAN
Date/Publication: 2019-04-16 10:32:57 UTC
