Multinomial Naive Bayes Formula. The number of times a given term appears in a document. Another useful example is multinomial naive bayes where the features are assumed to be generated from a simple multinomial distribution.
P c x p x c p c p x naive bayes are mostly used in natural language processing nlp problems. Laplacian smoothing will be used to determine the probability of a word. If a is a random variable then under naive bayes classification using bernoulli distribution it can assume only two values for simplicity let s call them 0 and 1.
The gaussian assumption just described is by no means the only simple assumption that could be used to specify the generative distribution for each label.
The number of times a given term appears in a document. Class sklearn naive bayes multinomialnb alpha 1 0 fit prior true class prior none source naive bayes classifier for multinomial models. The multinomial distribution normally requires integer feature counts. Multinomial naïve bayes uses term frequency i e.
