Laplacian Corrected Modified Naive Bayes

Fast linear classifier for nominal data

Laplacian Corrected Modified Naive Bayes (LCMNB) can be described as a discriminative version of naive Bayes. Specifically, it calculates the m-probability estimate of p(y|x_i) for each feature x_i and then multiplies these estimates to get the class predictions. Note that the implementation is only for nominal features.

For the reasoning behind the algorithm see:
https://www.ncbi.nlm.nih.gov/pubmed/15317458

For a detailed description of the algorithm see:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3846418/

For a bit of theory behind the m-probability estimates see:
https://dl.acm.org/citation.cfm?id=507538