Bayesian Filter

The Bayesian filter learns to detect spam by being shown content that has been identified as spam by the site administrator. The best way to describe this method is to quote Jeremy Andrews, the author of the Spam module.

The Bayesian filter does statistical analysis on spam content, learning from spam and non-spam that it sees to determine the likelihood that new content is or is not spam. The filter starts out knowing nothing, and has to be trained every time it makes a mistake. This is done by marking spam content on your site as spam when you see it. Each word of the spam content will be remembered and assigned a probability. The more often a word shows up in spam content, the higher the probability that future content with the same word is also spam. As most comment spam contains links back to the spammer's websites (ie. to sell Prozac), the Bayesian filter provides a special option to quickly learn and block content that contains links to known spammer websites.

For more information about Bayesian filtering, see http://en.wikipedia.org/wiki/ Bayesian_filtering.

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