I am new to machine learning and am trying to understand the different classifiers. I have searched the internet and books for a comprehensive explanation of the Multinomial Bayes classifier, but I just cannot seem to understand it.
First, I would like to know in which cases the multinomial distribution can be used. Do I understand correctly that it is mainly used for qualitative features (so not boolean or numeric)?
Second, I do not understand the equation for the conditional probability. The formula provided on the Wikipedia site https://en.wikipedia.org/wiki/Naive_Bayes_classifier under Multinomial naive Bayes is not comprehensive to me. What does pki stand for?