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.