From: "mouss" <[EMAIL PROTECTED]>
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)
Um, the cynic in me suggests we're seeing test conditions being tuned
to make a specific outcome appear.
{o.o}
