Hi! Just an idle thought: Why don't we start over and do everything differently? ;-)
No, really. I'm wondering whether the rules couldn't be dynamically re-scored like bayes auto-learning does. The benefits I see: - Rules the spammers have caught on to drop out automatically, instead having to wait for the next SA release, - the message score is a probability instead of a difficult to scale value, - it should be easy to just throw in some new rule and see how it fares: If it's not good enough, the value will stay at "indeterminate". I've seen an other thread about collecting custom rules; this could help to get them in without much cogitating about their merits. Perhaps there should be a confidence value in addition to the spamicity, for bayes as well as the rules (at least I think the bayes algorithm hasn't one and just cuts in when the overall token count is high enough): Not only count in how many spam and non-spam a token was seen, but how often it came up at all - so that, when a new rule matched once in a thousand mails, and that was spam, it doesn't necessarily mean the next mail it matches also is spam. If some rule stays at a low weight, it could be deactivated until further notice to save time. Of course, all this may be complete nonsense - the last few nights I mainly was coding instead of sleeping, and I fear that caffeine might affect my judgement... MfG, Ulrich -- Heinz Ulrich Stille / Tel.: +49-541-9400463 / Fax: +49-541-9400450 design_d gmbh / Lortzingstr. 2 / 49074 Osnabrück / www.design-d.de ------------------------------------------------------- This SF.Net email sponsored by: Parasoft Error proof Web apps, automate testing & more. Download & eval WebKing and get a free book. www.parasoft.com/bulletproofapps _______________________________________________ Spamassassin-talk mailing list [EMAIL PROTECTED] https://lists.sourceforge.net/lists/listinfo/spamassassin-talk
