Since NB is a generative classifier, we assume that the data points are all generated from a distribution, right?But since we can compute the MLE of p(x_i|y) by counting (MLE of p(x_i|y) = # of (x_i,y) / # of y), do we really need a specific distribution, if at all, to model the likelihood(p(x_i|y))?
Does Naive Bayes Classifier require assuming a specific distribution for training?
machine learning;naive bayes classifier