Matt Kettler wrote: > Neil wrote: > >> So maybe this is moving slightly off on a tangent, but: >> Why does auto-learn sometimes learn spam with a rating of X, but not >> spam with a rating of X+Y? Where's it's methodology? >> > > First, there's several rules involved here. > > To autolearn as spam *ALL* of the following must be met: > > -must have at least 3 points from header type rules > -must have at least 3 points from body type rules > -must not already match a low-scoring bayes rule in the existing > training (ie: BAYES_00) This prevents autolearning from contradicting > existing training. > -After recomputing the score of the message as if bayes and all userconf > rules were disabled (including changing the scoreset! This makes a big > difference in some cases.), that score must be over the spam learning > threshold. This prevents bayes from engaging in self-feedback or > feedback based on manual whitelists (which, if misconfigured would cause > a "bayes hangover" of mis-learned mail). > > Generally speaking, the score you see in the message header has only a > loose correlation with the score used for learning checks. > > Oh, one more rule I missed:
-The write lock for the bayes DB must be free. (ie: no other learning or expiry going on at the time). It will not block and wait for it, it will simply move on, but it will report autolearn=failed instead of autolearn=no. This prevents autolearning from log jamming your mail queue.
