Multinomial Naive Bayes Python. Naive bayes classifier with python naïve bayes classifier is a probabilistic classifier and is based on bayes theorem. I have used the counter python module to count the number of words that belong to each class and return them in a dictionary.
The multinomial naive bayes classifier is suitable for classification with discrete features e g word counts for text classification. Since we are employing the bag of words model for our naive bayes. Bnb naivebayes bernoulli true self.
However in practice fractional counts such as tf idf may also work.
One place where multinomial naive bayes is often used is in text classification where the features are related to word counts or frequencies within the documents to be classified. Data np array 0 0 0 1 1 0 1 1 bnb predict data array 0 0 1 1 this is the output that was expected from bernoulli s naive bayes. We discussed the extraction of such features from text in feature engineering. In machine learning a classification problem represents the selection of the best hypothesis given the data.
