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- new tweaks to the "Bayesian" learning classifier (the BAYES_* rules)
- new tweaks to the rescoring system (which is also a learning classifier, just at a higher level).
Traditionally, k-fold cross-validation uses a "train on k-1 folds, test on 1 fold"; we use that for testing our rescoring system. However, for the BAYES rules, we use "train on 1 fold, test on k-1 folds", as otherwise it can be hard to get a meaningful number of false positives and false negatives to be able to distinguish improvements in accuracy, because that classifier is very accurate when sufficiently trained.
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See RescoreTenFcv for a log of a sample 10-fold CV run against two SpamAssassin rescoring systems (the GA and the perceptron).
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