Naive Bayes Spam Filtering

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Sunnyvale, California, United States


Naive Bayes classifiers typically use bag of words features to identify spam e-mail, an approach commonly used in text classification. Naive Bayes classifiers work by correlating the use of tokens, with spam and non-spam e-mails and then using Bayes' theorem to calculate a probability that an email is or is not spam. Naive Bayes spam filtering is a baseline technique for dealing with spam that can tailor itself to the email needs of individual users and give low false positive spam detection rates that are generally acceptable to users.

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