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    Bayesian spam filtering has become a popular way to distinguish between legitimate emails and illegitimate spam emails, through a process that uses Bayesian statistical methods. It filters emails by classifying documents into categories. Based on the contents of the message in your email, the Bayesian spam filters calculate the probability of the message being a spam. They are much more robust than the normal content based filters, and their anti spam approach hardly has false positives.

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    ss that uses Bayesian statistical methods. It filters emails by classifying documents into categories. Based on the contents of the message in your email, the Bayesian spam filters calculate the probability of the message being a spam. They are much more robust than the normal content based filters, and their anti spam approach hardly has false positives.

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    age in your email, the Bayesian spam filters calculate the probability of the message being a spam. They are much more robust than the normal content based filters, and their anti spam approach hardly has false positives.

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    normal content based filters, and their anti spam approach hardly has false positives.

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    k tells you whether the email is a spam or not. To your eyes, there is ‘zero’ probability of a spam looking like a good email. How would it be if spam filters, too, worked in the same way!

    Bayesian Spam Filters

    Bayesian spam filters are what are known as scoring content-based spam filters. They try to work the way your eye does in identifying spam emails, by looking for words and other characteristics that typify spam. Every characteristic typical of spam is assigned a score, and the total spam score for the whole message is computed. Depending on the type of Bayesian spam filter you are using, it may also look for legitimate email characteristics, th

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