Naive Bayes classifier

Naive Bayes is a probabilistic classifier based on Bayes' theorem and the assumption that features are conditionally independent given the class.

[P(C\mid x_1,\ldots,x_n)\propto P(C)\prod_iP(x_i\mid C)]

For a new example, calculate this score for each class and choose the largest posterior probability. Variants include Gaussian Naive Bayes for continuous features, Multinomial Naive Bayes for counts/text, and Bernoulli Naive Bayes for binary features. It is fast and effective for many text-classification tasks, but correlated features can make its probability estimates inaccurate.