Gabriel Wachman a écrit : > A colleague and I are writing a paper about a spam filter he developed. > We'd like to compare it against various open source filters, including > SpamAssassin. The methodology we are using is to train the filter on a > set of messages, and then test it on an independent set of messages. The > key is that the filter cannot update itself at all after training. > > In my user_prefs: > bayes_auto_learn 0 > bayes_learn_during_report 0 > bayes_path SOME_PATH
why disable auto learning? Are you sure what you want isn't: - run in supervised mode (human to correct the decisions) on N messages (the training set) and then - run in unsupervised mode (no human correction) on M other messages (The validation set)
