On Freitag, 23. Juni 2006 21:58 Brian Godette wrote: > Also note that a large amount of your score was from > DCC, Razor, and URIBLs that didn't hit at the initial receipt of this > message.
Yes, another reason to use greylisting *g* If I counted correct, it should still - but just - have been marked as SPAM. And it gave BAYES_99, which you could score 4.9 if you want. I don't need it, as there's almost never spam coming thru.. > This is only really an issue for people who use site-wide bayes as > per-user bayes has a lower chance of having seen true ham similar to > the encapsulated ham. Are you sure about that? It would have to be a message that was ham, have (nearly) the same content, autolearn must be on and the message must have been learned. That's a lot of "if...and.." statements. I use sitewide bayes (hand trained), and got BAYES_99. Yes, I have autolearn on, but I do a lot of hand crafted training, and modified the default values for learn_as_(spam|ham). mfg zmi -- // Michael Monnerie, Ing.BSc ----- http://it-management.at // Tel: 0660/4156531 .network.your.ideas. // PGP Key: "curl -s http://zmi.at/zmi3.asc | gpg --import" // Fingerprint: 44A3 C1EC B71E C71A B4C2 9AA6 C818 847C 55CB A4EE // Keyserver: www.keyserver.net Key-ID: 0x55CBA4EE
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