By "not a factor" I meant that it was scoring midrange, so did not end up contributing to the final score. But you're right, the database is screwy. Largely because of my problem that spam scores too low. We have auto-learn, and many spams don't make a high enough score to be auto-learned as spam. In addition, some spams actually score low enough (see the habeas problem I mentioned earlier) to be auto-learned as ham :-(
Any pointers on how to get the non-bayes spam score up, so that auto-learn will be more useful? Thanks... > From [EMAIL PROTECTED] Wed Mar 10 15:00:31 2004 > > At 05:56 PM 3/10/2004, [EMAIL PROTECTED] wrote: > >Probably 50% of what appears to > >the eye as obvious spam gets scored in the 0.4 to 4.9 range. We > >had some that scored around -4.x because it had Habeas headers in > >it that apparently were not detected as fake. > > >So we're using default scoring for almost everything, and would > >rather stay with the defaults as much as possible rather than start > >hacking at scoring to artificially inflate the scores. > > > >For the most part, bayes is not a factor (I'm hand-running messages > >with the -D flag to try to see what's going on). > > Um... that's a definite mis-statement. Bayes almost certainly IS a factor. > Anything "obviously spam" should be getting BAYES_90 or BAYES_99.. if you > are getting lots of FN mail that's not scoring high in bayes, you might > want to examine your training. > > >
