From: KÄrlis Repsons <karlis.reps...@gmail.com> Date: Sat, 30 Jan 2010 14:07:16 +0000 On Saturday 30 January 2010 13:54:14 Jeff Mincy wrote: > Retrain the message correctly in Bayes. Bayes will catch on to this > after a few times. The subject alone should be a strong enough clue > for bayes (I get BAYES_80 on this partial sample), so it looks like > you are doing only autolearn and not correcting messages that were > learned incorrectly. > -jeff I couldn't figure out how to get an unadulterated version of the message from the spamalyser.com link you posted in a previous message. I tried this wget -O - -q http://spamalyser.com/v/5cbffujq/original.txt pastebin has a simple way to download the original. Anyway, I eventually got something.
Hmm, well, I just started with SA, so my filters aren't much trained yet. The thing is, I didn't believe its the Bayes filter to be used for that case! Bayes is an incredible tool, but only if you let it. The worst thing you can do to bayes is mistrain it by learning spam messages has ham. The other bad thing is to limit the number of messages that it learns from. Because I still think, that its not correct to train SA filter on that letter as spam! It can contain words, which simply should not contribute to be more "spam", no? Thats not a problem? No, that is not a problem. Yes, spam contains words, some of those words will also occur in ham. Bayes will figure out which words are spammy and which are hammy and which occur in both. First start with training Bayes and then check if DCC and network tests are enabled. Anyway, I get the following. BAYES_99,DCC_CHECK,RCVD_IN_BL_SPAMCOP_NET,RCVD_IN_FIVETEN_SPAM,RCVD_IN_NIXSPAM,RCVD_IN_UCEPROTECT1,RCVD_IN_UCEPROTECT2,RCVD_IN_UCEPROTECT3,BOTNET,BOTNET_BADDNS Botnet/FIVETEN/NIXSPAM/UCEPROTECT are additional rules added. -jeff
