If it's already 100% sure that it's spam, how is it helpful to train it that it's spam? It's not like it's going to be 110% sure that it's spam. It's already trained!
Not trying to be a wise-ass, I've just seen this question come up fairly often, and can't wrap my head around it. -tom > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On > Behalf Of Chris Barnes > Sent: Wednesday, November 05, 2003 2:09 PM > To: [EMAIL PROTECTED] > Subject: [SAtalk] a new rule > > How hard would it be to create a new rule for BAYES scoring > that IS used by autolearn? > > Specifically, when I see this: > * BAYES_99 BODY: Bayesian spam probability is 99 to 100% > * [score: 1.0000] > > in the header, I'm fairly comfortable with having it autolearnt and > letting my .procmailrc script send it straight to /dev/null. > However, > since BAYES scores are not used in deciding whether or not > autolearn is used, this rarely happens. > > So a new rule of BAYES_100 (for scores that are 100%), that > is used would be helpful. How? > ------------------------------------------------------- This SF.net email is sponsored by: SF.net Giveback Program. Does SourceForge.net help you be more productive? Does it help you create better code? SHARE THE LOVE, and help us help YOU! Click Here: http://sourceforge.net/donate/ _______________________________________________ Spamassassin-talk mailing list [EMAIL PROTECTED] https://lists.sourceforge.net/lists/listinfo/spamassassin-talk
