> 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... -- Matus UHLAR - fantomas, uh...@fantomas.sk ; http://www.fantomas.sk/ Warning: I wish NOT to receive e-mail advertising to this address. Varovanie: na tuto adresu chcem NEDOSTAVAT akukolvek reklamnu postu. Remember half the people you know are below average.
