Bayesian Spam Filters Explained

In a word Bayesian spam filters are "intelligent". Bayesian spam filters are intelligent in so far as they're capable of comparing two sets of information and acting on the result. This is in direct contrast to the vast majority of other spam filters who use pre-built rules to decide which e-mail is spam and which is not.

Bayesian spam filters can take one group of legitimate e-mail and another group of spam and compare the values and data of each. The definition of legitimate e-mail that it creates at the end of this comparison session is what it uses going forward to scan your inbox for spam.

FYI Bayesian spam filters are named after Thomas Bayes an 18 century cleric who created something known as Bayes Theorem. In summary Bayes Theorem is as follows: .."in statistical inference to update estimates of the probability that different hypotheses are true, based on observations and a knowledge of how likely those observations are, given each hypothesis." In plain English it looks for obvious repeating patterns to form an "opinion" on something. In spam filter terms that "opinion" becomes a rule which keeps you spam free (or pretty close :-)

The really neat thing about Bayesian filters is that they're capable of learning. For example if they decided to block an e-mail because the filter perceived it as junk but the user marked it as valid mail the Bayesian filter then knows not to block that type of e-mail in the future. So, in time, this type of spam filter learns enough to block spam far more effectively.