On Sun, 25 Sep 2011 09:28:32 -0700 Marc Perkel <supp...@junkemailfilter.com> wrote:
> Each rule combo is then looked up for how often it occurs in spam and > how often it occurs in ham. Then the results are combined into some > sort of likelihood of being spam or ham. We looked at (and even implemented) some "meta-tokens" that we throw into Bayes. We found that trying to be too clever is self-defeating; plain old Bayes is generally better at locking on to spam/ham trends than feeding it derived data. Anyway, in theory, SA's genetic weighting algorithm should give you the desired results, though I suppose a Bayes-like approach might tweak the rule weights for your specific mail stream. Regards, David.
