fastNaiveBayes: Extremely Fast Implementation of a Naive Bayes Classifier
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.
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:10.3115/1067807.1067848>. Any issues can be
submitted to: <https://github.com/mskogholt/fastNaiveBayes/issues>.
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