Mastering Machine Learning with scikit-learn - Second Edition

Naive Bayes

In the first section of this chapter, we described Bayes' theorem. Recall that it is given by the following:

Let's rewrite Bayes' theorem in terms that are more natural for a classification task:

In the preceding formula, y is the positive class, x₁ is the first feature for the instance, and n is the number of features. P(B) is constant for all inputs, so we can omit it; the probability of observing a particular feature in the training set does not vary for different test instances. This leaves two terms: the prior class probability, ...