Naive Bayes is a probabilistic model, which makes predictions by computing the probability of a data point that belongs to a given class. A naive Bayes model assumes that each feature makes an independent contribution to the probability assigned to a class (it assumes conditional independence between features).

Due to this assumption, the probability of each class becomes a function of the product of the probability of a feature occurring, given the class, as well as the probability of this class. This makes training the model tractable and relatively straightforward. The class prior probabilities and feature conditional probabilities are all estimated from the frequencies present in the dataset. Classification is performed ...