Bayes' Theorem provides a convenient framework for predicting a binary response s ∈ {−1, 1} from a feature vector x: For a labeled sample of data (x i , s i ), i = 1, ..., n, a class's marginal probability π k can be estimated trivially as the proportion of training samples belonging to the class.
the corresponding drawback to such an approach is that its predictions are not validated on actual documents.