Dear SA users, I've had an offlist comparison of bayes DBs, and we found some interesting differences. We're trying to find out why bayes on server #1 makes better scores.:
Server #1 local.cf (SA 3.1.1): bayes_expiry_max_db_size 2000000 bayes_auto_expire 0 bayes_file_mode 0777 bayes_auto_learn_threshold_spam 8.00 bayes_auto_learn_threshold_nonspam 1.0 Server #1 bayes files: -rw-rw-rw-+ 1 vscan vscan 19738624 May 10 10:04 bayes_db_seen -rw-rw-rw-+ 1 vscan vscan 41697280 May 10 10:04 bayes_db_toks Server #1 bayes dump: 0.000 0 93053 0 non-token data: nspam 0.000 0 53428 0 non-token data: nham 0.000 0 1261864 0 non-token data: ntokens Server #2 local.cf: bayes_auto_learn 1 bayes_learn_to_journal 1 bayes_auto_expire 1 ok_languages de en es ok_locales en Server #2 bayes files: 21M 2006-05-10 10:20 bayes_seen 5,3M 2006-05-10 10:20 bayes_toks Server #2 bayes dump: 0.000 0 155791 0 non-token data: nspam 0.000 0 80523 0 non-token data: nham 0.000 0 129852 0 non-token data: ntokens From the numbers I would say that server #2 had learned more spam+ham, but has about 1/10th of tokens. That server is also far less accurate with bayes than server #1. Could the ntokens be the reason? With the new SPAM this last weeks, that tries to poison bayes, it could maybe be effective with the default of 150.000 tokens? Another tip for all: With server #1 setting bayes_auto_learn_threshold_spam 8.00 you could expect this message to be autolearned: > X-Spam-Status: Yes, hits=8.7 required=5.0 tests=BAYES_99=3.5, > HTML_MESSAGE=0.001,HTML_MIME_NO_HTML_TAG=0,HTML_TAG_EXIST_TBODY=0.282, > MIME_HTML_ONLY=0.389,RELAY_DE=0.01,REPLY_TO_EMPTY=0.512, > SARE_FORGED_EBAY=4 autolearn=no bayes=1.0000 But it is autolearn=no. This shows, that manual re-feeding SPAM can be effective for your Bayes, because this sure-is-spam would not have been learned automatically. Since it's already BAYES_99, you could say "don't bother, I'll be fine" *g* but bayes needs to be trained permanently, because tokens time out... And why was SARE_FORGED_EBAY set down to 4? It was so nice at 100+... Also, we set bayes_expiry_max_db_size to 50000, and made sa-learn --force-expire --sync But still those numbers: > 0.000 0 242424 0 non-token data: nspam > 0.000 0 313252 0 non-token data: nham > 0.000 0 134001 0 non-token data: ntokens Why are still 134k tokens there? mfg zmi -- // Michael Monnerie, Ing.BSc ----- http://it-management.at // Tel: 0660/4156531 .network.your.ideas. // PGP Key: "lynx -source 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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