so it doesnt make a difference if you have inordinately larger amounts of one than the other?? I would have thought it would've worked better with more ham...
i read somewhere on the list thats its best to balance.
you'll get conflicting answers to this question. The only real answer that i can tell is "see what works best on your system" If you get significantly more spam than ham, and autolearning is enabled, then you will have signficantly more spam tokens than ham. Over here at the hospital where i work, we get significantly more ham than spam so my numbers are usually the opposite from everyone elses. This goes to show that even with opposite ratios, the bayes system still works properly. This should be argument enough that you dont need to have a balance in the number of spam/ham tokens.
on a related note why is my autolearn not funtioning properly???
good question. Im not sure what the causes of autolearn=failed are. But i did happen to notice that you appear to have ALL_TRUSTED firing on every email you receive. There may be larger issues with the setup here. Posting on the list (and not just to me) may provide you will more answers as many more people will see the message as well.
-Jim
bash-2.03$ sa-learn --dump magic
0.000 0 3 0 non-token data: bayes db version
0.000 0 1077 0 non-token data: nspam
0.000 0 427 0 non-token data: nham
0.000 0 120915 0 non-token data: ntokens
0.000 0 1082126382 0 non-token data: oldest atime
0.000 0 1101307652 0 non-token data: newest atime
0.000 0 1101307670 0 non-token data: last journal sync atime
0.000 0 1100189181 0 non-token data: last expiry atime
0.000 0 0 0 non-token data: last expire atime delta
0.000 0 0 0 non-token data: last expire reduction count
bash-2.03$ tail -f /var/log/syslog|grep autolearn
Nov 24 14:56:12 elisha spamd[5125]: result: . -1 - ALL_TRUSTED scantime=2.8,size=1755,mid=<[EMAIL PROTECTED]>,autolearn=failed
Nov 24 14:56:15 elisha spamd[5125]: result: . -1 - ALL_TRUSTED,FROM_ENDS_IN_NUMS,NO_REAL_NAME scantime=0.6,size=1155,mid=<[EMAIL PROTECTED]>,autolearn=failed
Nov 24 14:56:27 elisha spamd[6919]: result: . 0 - ALL_TRUSTED,FROM_ENDS_IN_NUMS,MISSING_SUBJECT,NO_REAL_NAME scantime=2.8,size=1329,mid=<[EMAIL PROTECTED]>,autolearn=no
Nov 24 14:56:29 elisha spamd[7794]: result: . -1 - ALL_TRUSTED,FROM_ENDS_IN_NUMS scantime=2.5,size=1705,mid=<[EMAIL PROTECTED]>,autolearn=failed
Nov 24 14:56:31 elisha spamd[5467]: result: . 0 - ALL_TRUSTED,FROM_ENDS_IN_NUMS,J_CHICKENPOX_21,J_CHICKENPOX_24,NO_REAL_NAME scantime=5.2,size=4798,mid=<[EMAIL PROTECTED]>,autolearn=failed
Nov 24 14:56:32 elisha spamd[6919]: result: . -1 - ALL_TRUSTED,FROM_ENDS_IN_NUMS,NO_REAL_NAME scantime=2.5,size=2668,mid=<[EMAIL PROTECTED]>,autolearn=failed
Nov 24 14:56:34 elisha spamd[7794]: result: . -1 - ALL_TRUSTED scantime=0.6,size=32341,mid=<[EMAIL PROTECTED]>,autolearn=failed
Nov 24 14:56:35 elisha spamd[5467]: result: . 2 - FORGED_HOTMAIL_RCVD2,FORGED_RCVD_HELO,MISSING_MIMEOLE,NO_REAL_NAME,PRIORITY_NO_NAME,RCVD_IN_SORBS_DUL scantime=0.6,size=78030,mid=<[EMAIL PROTECTED]>,autolearn=no
Nov 24 14:56:36 elisha spamd[8365]: result: . -1 - ALL_TRUSTED,HTML_MESSAGE,HTML_TAG_EXIST_TBODY scantime=8.5,size=12218,mid=<[EMAIL PROTECTED]>,autolearn=failed
Nov 24 14:56:38 elisha spamd[6919]: result: . -1 - ALL_TRUSTED scantime=1.1,size=14404,mid=<[EMAIL PROTECTED]>,autolearn=failed
Nov 24 14:56:38 elisha spamd[5467]: result: . -1 - ALL_TRUSTED,HTML_60_70,HTML_MESSAGE scantime=1.6,size=2221,mid=<[EMAIL PROTECTED]>,autolearn=failed
