As I understand it, the thing to do is to train on messages that contain those words. That is, if you receive a message that contains those words and SpamBayes classifies it as spam or possible spam, tell SpamBayes that it's actually ham. Alternatively, you could probably parse through the code to understand the database design and hack up something to add some special tokens to the database. Heck, you could change the code itself to give special treatment to your whitelist tokens. The source is readily available.
I don't recommend any of the above, though. If you somehow receive a spam message with one of your whitelist words in it, the first approach would require you to mislead SpamBayes about what you consider to be spam, and the others seem very error-prone. Lots of people have tried to find ways to make SpamBayes smarter. As near as I can tell, no one has found a way to make it consistently perform better in a long time. Does it matter that it's dumb if it gives good results? -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Luca Benassi Sent: Thursday, March 08, 2007 6:42 AM To: [email protected] Subject: [Spambayes] interacting with dbm I've serched a bit in doc, faq and old messagges but ... no luck :] This is my question: can I populate the dbm with my list of *safe* (good) words? I'd like to, sort of, whitelist a group of words. Thx in advice, Luca -- Dr. Luca Benassi Laboratori Guglielmo Marconi Via Porrettana 123, 40037 Pontecchio Marconi (BO) - ITALY Phone:+39-0516781934 Fax:+39-051846479 e-mail: [EMAIL PROTECTED] Systems & Networks Division _______________________________________________ [email protected] http://mail.python.org/mailman/listinfo/spambayes Check the FAQ before asking: http://spambayes.sf.net/faq.html _______________________________________________ [email protected] http://mail.python.org/mailman/listinfo/spambayes Check the FAQ before asking: http://spambayes.sf.net/faq.html
