Naive Bayes

Description

Naive Bayes is a probabilistic algorithm that is commonly used for text classification. It is based on Bayes' theorem, which states that the probability of a hypothesis (in the text-classification case, a document belonging to a particular class), given some observed evidence (in this case, the words in the document), is proportional to the probability of the evidence given the hypothesis times the prior probability of the hypothesis.

Naive Bayes assumes that the features (words) are independent of each other given the class label, which is where the "naive" part of the name comes from.