Hello Mailing, Tuesday, June 21, 2005, 10:48:44 AM, you wrote:
MLANC> Hi! MLANC> I have a little problem with spam recognition. I have re-learned MLANC> SpamAssassin (deleting old file from ".spamassassin" directory, to clear MLANC> old information) and it worked really nice... but after few days, the MLANC> efficency of SpamAssassin degrades from >90% of spam correctly MLANC> identified to a 60%... I tried to learn it again with new, not MLANC> recognized spam (and with all new ham, to respect a 1:1 - about - ratio MLANC> of spam:ham) but without any result. My experience is the opposite -- after wiping a Bayes database SA is initially 70%-80% accurate, and then rises steadily to 95% and better (better = with SARE rules). I'm guessing you may have auto-learn enabled with the default limits, and spam that sneaks by with 0.0 or 0.1 scores are learned as non-spam, polluting your database. If you have reliable negative-scoring ham rules (which generally are domain- or user-specific, then set your auto-learn ham threshold to some negative score (-0.2 or -0.5 or something like that). If you have no reliable negative-scoring ham rules, then turn off auto-learn and ONLY use sa-learn manually as you describe above. That may take care of your problem. Alternately, are you using SARE rules? Start with the most reliable SARE rules files, expand slowly, and they'll probably help you avoid Bayes degredation. Bob Menschel
