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Evaluate these features with the Naive Bayesian Chain Rule
learning: each feature is bucketed into one of one million buckets in one of two bucket files (one spam, one nonspam)
Classifying: the comparble bucket counts of the two files generate rough estimates of each feature's 'spamminess'
P(F|C) =0.5 + ( |Fc| - |F~c| ) / ( 2 * MaxF )