jdow writes: > From: "Alexander Piavka" <[EMAIL PROTECTED]> > > > On Sat, 15 Jul 2006, Magnus Holmgren wrote: > > > >> On Tuesday 11 July 2006 23:16, Alexander Piavka took the opportunity to > >> write: > >> > Hi , i'd like to know if its possbile and how, to ignore specific rule > >> > scores (like ALL_TRUSTED) then calculating the autolearn threshold for > >> > spam and ham? > >> > >> "Like" ALL_TRUSTED, eh? If you have a problem with ALL_TRUSTED you likely > >> have > >> a bad trusted_networks setting. Adding a host to trusted_networks means > >> that > >> you trust it not to forge headers and not to originate spam, meaning that > >> if > >> ALL_TRUSTED fires then the message *should* definitely be ham, otherwise > >> your > >> assumption that the host can be trusted is wrong. > > > > No i've no problem with ALL_TRUSTED , it's just i thoght it's not a good > > idea to learn every mail from trusted networks as ham, i wanted to make a > > bayes autolearn independent of the sending source and thus ignore > > ALL_TRUSTED > > and some more tests. Since this way bayes would learn from much more ham > > messages than spam messages,esspecialy since most spam messages we get are > > the same. Thus i thougth since the bayes databese size is limited it > > should have learn from at least as much spam mail as ham, to have more > > spam mails detected by bayes. > > But probably i'm wrong or not? > > One might say two things. The first is a startled "Well duh!" The second > is, "if you have ALL_TRUSTED" appear as a rule hit on every message then > you're being silly. > > ALL_TRUSTED does not mean a damn thing with respect to whether a message > is ham or spam. It just says that the received headers are likely to be > accurate in as much as "you" or a "trusted agent" oversees the header > generation.
um, no, ALL_TRUSTED means that all of the hosts that relayed the mail were trusted -- including the very first, originating host. This should not happen unless you list a spammer's machine in trusted_networks. --j.
