What is Bayesian Filter and how it works?
Bayesian filters are more or less based on the Bayes rule, a theory of conditional probability that estimates the likelihood of an event (hypothesis) given the certainty of another event (evidence). Basically, the rule says that the likelihood of an event occurring in the future can be inferred from the number of times it occurred in the past. The Bayesian filter works on studying the e-mail and also the spam that you have received in the past. These create two collections a good collection, consisting of all the real e-mails you received and the bad collection which consists of all the spam you have received in the past. It counts the number of times each word in the good collection occurs in the good collection and creates a table. It does the same for the bad collection with the end result being two tables, one for the good collection and one for the bad collection. The filter uses these tables when constructing probabilities for future e-mail it encounters being spam. In other word
