> Hi, > > One thing I do not understand regarding AWL and BAYES. > When a message is reported to me as spam and was not > marked as spam, I test is using debug before and after > sa-learn. Each time I do this, BAYES_99 does hit, but > they will also include AWL. > > 1. Does anyone understand why this happens? > 2. I also noticed that when using "spamassassin -D" on a > message, I sometimes see a nice report like below (2nd > example) but other times it doesn't show report > formatted. Any ideas on this one?
If I understood you correctly.. In your samples, the first run gets 3.9 points, which is less than needed to classify the post as spam. The second run (after the learning) gets 5.2 points, which is more than needed to classify the post as spam. Your configuration prints the formatted report only for spam. There is no point in delivering reports to users for email which is not spam. The limit for spam is 5.0 points (as the report says, 5.0 required), which is the default and a pretty good value. > > Here are an example of two spam report headers for the > same message. > > Before sa-learn: > > X-Spam-Status: No, score=3.982 tagged_above=-9999 > required=5 tests=[ADVANCE_FEE_1=0, BAYES_60=1, > SUB_HELLO=2.141, UNDISC_RECIPS=0.841] X-Spam-Score: 3.982 > X-Spam-Level: *** > > After sa-learn: > > Content analysis details: (5.2 points, 5.0 required) > > pts rule name description > ---- ---------------------- > -------------------------------------------------- > 2.1 SUB_HELLO Subject starts with "Hello" > 0.8 UNDISC_RECIPS Valid-looking To > "undisclosed-recipients" > 3.5 BAYES_99 BODY: Bayesian spam > probability is 99 to 100% > [score: 1.0000] > 0.0 ADVANCE_FEE_1 Appears to be advance fee > fraud (Nigerian 419) -1.2 AWL AWL: > From: address is in the auto white-list > > Thanks, > Randy Ramsdell
