> Hoover Chan wrote:
> >The threshold was set to 6.6 (cf. required=6.6). The message this was 
> >attached to was very definitely junk. This kind of situation got me 
> >curious about the whole thing where any positive spam score is set as the 
> >threshold but seeing junk mail coming in with negative scores.

On 20.03.09 16:14, Jesse Stroik wrote:
> You are getting negative scores for auto white list and for bayes_00. 
> It's a matter of taste and what you believe makes sense, but I don't 
> consider bayes to be all that accurate (since there are methods for 
> defeating bayes, poisoning bayes, etc).

What methods? afaik the bayes poisoning turned out to be not working
(and even could help us do detect spam when using hapaxes).

And I don't know anything about defeating BAYES, if properly trained.
Maybe leaving things on autolearn is not a good idea, when not updating
scores (sa-update) and/or not using network checks.

> As such, I don't allow Bayes to 
> assign negative scores or positive scores within a couple of points of 
> the threshold.  You can do so by assigning scores like this:
> 
> score BAYES_00  0
> score BAYES_05  0
> score BAYES_20  0
> score BAYES_40  0

However, it's better not to do that and solve your problem by proper
training the databbase. I found BAYES to be very effective for some wanted
mail sent by lame mailers...

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