As you can see from the response I just posted, I'm not using MySQL for bayes (albeit, maybe I should be, that seems very convenient.)
>You do not need to include the X-Spam-* header fields as they are >stripped before learning. Thanks. I'll pull those out. -----Original Message----- From: Duane Hill [mailto:[EMAIL PROTECTED] Sent: Friday, August 01, 2008 4:27 PM To: users@spamassassin.apache.org Subject: Re: autolearn=yes but sa-learn dump magic shows no new spam On Fri, 1 Aug 2008, Brett Millett wrote: > I've been googling quite a bit today to find the answer to what I'm > seeing that is happening on my mail server. However, I just can't seem > to find a definitive answer. When looking at my mail logs I see a number > of autolearn=spam, however when I run "sa-learn --dump magic" nspam does > not increment. If I run sa-learn manually, nspam increments. Is this > normal or should each autolearn=spam indicate that nspam should > increment by one. I can only speculate this would have something to do with the user autolearn is running against. I'm going to assume you are using MySQL as you did not state. Have you tried going into MySQL and: select count(*) from bayes_vars; to see how many usernames are in the table? Perhaps you can post the startup parameters spamd is using. Also how spamc is being called (if that is the case). That may shed more light on why you are getting the results you are. > Here is my local.cf file as it pertains to bayes and autolearn: > > use_bayes 1 > bayes_auto_learn 1 > bayes_ignore_header X-Bogosity > bayes_ignore_header X-Spam-Flag > bayes_ignore_header X-Spam-Status You do not need to include the X-Spam-* header fields as they are stripped before learning. > bayes_auto_learn_threshold_nonspam -0.1 > bayes_auto_learn_threshold_spam 5.0 > use_auto_whitelist 1 > bayes_use_hapaxes 1 > bayes_min_ham_num 150 > bayes_min_spam_num 150 > score BAYES_00 -3 > score BAYES_05 -1 > score BAYES_95 6 > score BAYES_99 9 > score BAYES_20 -0.8 > score BAYES_40 0 > score BAYES_50 1.567 > score BAYES_60 3.515 > score BAYES_80 3.608 -d
