Chavdar Videff wrote:
Your bayes may be hosed. You may want to tune the set score that autolearn learns upon. It also seems you are using an older version of SA. Upgrade to take advantage of URI BLs. With out the headers from the mails that fp/fn'd it may be hard to guess as to what the real situation is.Dear List,I know these are subject of the FAQ and the documentation, yet after I read all of it I didn't get an answer to the following questions:1. At our site we get approx. 1000 spam a week. Most of it is rated below 2.0 points and gets through (even if we set required hits to 3 and 2 for certain mailboxes).2. Mail composed as HTML is rated as spam for the above reason. What can we do to improve the situation and boost the performance of SA.I assume that if we set required hits below 5.0, ham messages composed as HTML will be rated as spam. However, the overwhelming number of spam rated below 4, 3, 2 and even 1 points that we receive renders spamassassin useless for our mail-server.We sort ham and spam and run sa-learn daily in order to train SA, we feed the low-rated spam and ham that is not rated correctly to sa-learn without any success: most messages (that are repeated) continue to go through.Please help.Why doesn't sa-learn help. We thought that if we submit to sa-learn a messages that was mistaken, the next time a message that is the same or from the same address will be sorted correctly.Following is the configuration file (debian sid, sendmail, sitewide configuration of SA).mail1:/home/chavdar# cat /etc/mail/spamassassin/local.cf # This is the right place to customize your installation of SpamAssassin. # # See 'perldoc Mail::SpamAssassin::Conf' for details of what can be # tweaked. # ########################################################################### # # rewrite_header Subject *****SPAM***** # report_safe 1 # trusted_networks 10.50 # lock_method flock required_hits 3 rewrite_subject 1 report_header 1 use_terse_report 1 defang_mime 0 report_safe 0 use_bayes 1 auto_learn 1 Regards Chavdar Videff
HTH -- Thanks, JamesDR
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