Multinomial Naive Bayes Classifier. Two event models are commonly used. Naive bayes classifier for multinomial models.
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Naïve bayes which is computationally very efficient and easy to implement is a learning algorithm frequently used in text classification problems. For class j word i at a word frequency of f. Multinomial naive bayes classifier combining probability distribution of p with fraction of documents belonging to each class.
Naive bayes classifier for multinomial models.
The multivariate event model is referred to as multinomial naive bayes. Naive bayes classifier for multinomial models. Two event models are commonly used. The features predictors used by the classifier are the frequency of the words present in the document.
