Potential new auto-learning strategy

["Gray, Richard" <ri...@dns.co.uk>]

I saw an article a while back about some DJs who were using perl as a
mixing tool by writing perl code that edited itself while it ran in a
loop. I thought this was kind of cool. 
 
I studied AI at university, and remember a good bit of discussion
regarding feedback systems.
 
So, to combine the two, I was thinking of how to use SA in a similar
structure, and propose a dynamic weighting system for SA rules. Consider
the scores that a base installation of SA gives to its rules, but when
shown messages to learn from, it modifies the score weighting of the
rules rather than the bayes system.
 
I'll not throw out a discussion regarding learning rates and so, but I
can imagine the logic being loosely based on how much influence the rule
had on the total score, the distance of the final result from the
spam/ham boundary, and the learning rate chosen by the administrator.
 
Any feedback?
 
R


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