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:
For a detailed description of the algorithm see:
For a bit of theory behind the m-probability estimates see:
Jan Motl (2020). Laplacian Corrected Modified Naive Bayes (https://www.mathworks.com/matlabcentral/fileexchange/69769-laplacian-corrected-modified-naive-bayes), MATLAB Central File Exchange. Retrieved .