Naive Bayes spam filtering - Wikipedia

Naive Bayes classifiers are a popular statistical technique of e-mail filtering. They typically use bag-of-words features to identify email spam, an approach commonly used in text classification. Naive Bayes classifiers work by correlating the use of tokens (typically words, or sometimes other things), with spam and non-spam e-mails and then using Bayes' theorem to calculate a probability that an

[IanLewis]

Bayesian spam filtering (pronounced /ˈbeɪzi.ən/ BAY-zee-ən, after Rev. Thomas Bayes) is a statistical technique of e-mail filtering. It makes use of a naive Bayesian classifier to identify spam e-mail.