On Tue, Sep 07, 2004 at 02:32:42PM -0600, Chris Blaise wrote: > The rules were ALL_TRUSTED,MISSING_DATE,USER_IN_BLACKLIST and I > think since "ALL_TRUSTED" is a negative value. > > Am I missing something about how auto-learn should consider this? > > Is there a reason why it doesn't consider such a message as spam, > soley on the score? I realize that it won't learn spam if the header and > body aren't at least 3 each, but for such a high score, it seems like it > should be able to disregard that to say, "This is huge; learn it as spam."
This has been convered many times. It's probably in the wiki, and definitely
in the documentation:
[...]
bayes_auto_learn ( 0 | 1 ) (default: 1)
[...]
Note that certain tests are ignored when determining whether a mes-
sage should be trained upon:
- rules with tflags set to 'learn' (the Bayesian rules)
- rules with tflags set to 'userconf' (user white/black-listing
rules, etc)
- rules with tflags set to 'noautolearn'
Also note that auto-training occurs using scores from either score-
set 0 or 1, depending on what scoreset is used during message
check. It is likely that the message check and auto-train scores
will be different.
As always though, run with -D and you'll find out plenty. ;)
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