http://bugzilla.spamassassin.org/show_bug.cgi?id=3785





------- Additional Comments From [EMAIL PROTECTED]  2005-09-16 16:46 -------
(In reply to comment #1)

That wouldn't quite get where I was hoping to go, because the real problem is
with  low scores for high BAYES_* values.  I haven't looked at the BAYES_*
scores in 3.1.0 yet, but in 3.0.x I frequently get spams that hit BAYES_99 but
pass through because they hit nothing else.  Switching rulesets only when Bayes
can't make up its mind would not address that problem; rather, I'm trying to
discover rules that have a different (better) S/O ratio when tested only on
"likely" spam (as opposed to when tested on all messages in the input set).

Consider, for example, a rule that looks for "remove me" phrases or URLs.  If
the entire input set contains mailing list messages, the S/O of such a rule may
be pretty poor.  But if you look only at the subset that is already deemed
spammy by Bayesian analysis, mailing list messages might already have been
filtered out, and having a remove-me phrase could become more significant.



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