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Bibulus altogether, and taking the two names of Caesar to make out the
tracts of cultivated land, the slopes of the hills and the mountain
him on business of common interest, he would state the particulars that
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Bayesian filtering takes folders of known spam and known ham and identifies words or phrases ("tokens") that only show up in spam and tokens that only show up in ham. When a new message is being scored in the future, if it contains a lot of spammy tokens, it spam score goes up. If it contains a lot of hammy tokens, its spam score goes down. This is a much better approach than static phrase identification as it handles the case where "Nigeria" might be a legitimate word in an email to a travel agent's office, or "breast" would be legitimate in an email to a women's clinic.