Hi! Sorry, its me again, bayes learning seems again 'biased', this time to spam, may be by picture spams?
After installing new modules to catch picture spams, the scores of those seem to go high enough to autolearn those included random texts. So I seem to be in a fix, eighter learning 'everything is spam' (because random tokens hit randomly -> everything) or switching off 'bayes'(learning) and letting through a lot of Spam. Spammers would love both, my users will complain. I have so far no chance to get enough spam+ham from the users to 'hand-train instead of autolern'. (Not allowd to read userboxes, no time to coordinate and crosscheck extra ham-folders of users). Is there a chance to create a rule to autolearn mail which is surely local (and not forwarded by local users, lest they forward spam). I looked into the rules-files and found lots of 'relay-checks', but could not find out, how to adapt one to this idea. I could add a negative score to mails which contain anly out mailhub's headers. Pointers, Examples, any Help welcome! Yours Stucki, postmaster at math/inf/mi.fu-berlin.de -- Christoph von Stuckrad * * |nickname |<[EMAIL PROTECTED]> \ Freie Universitaet Berlin |/_*|'stucki' |Tel(days):+49 30 838-5 57 78| Mathematik & Informatik EDV |\ *|if online|Tel(else):+49 30 77 39 66 00| Arnimallee 6 / 14195 Berlin * * |on IRCnet|Fax(alle):+49 30 838-75 454/