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?
>
> Even if your trusted_networks setting is correct and you feel that mail coming
> through all trusted hosts isn't representative, I don't think it would hurt
> learning it.
>
> But to answer your question - use the noautolearn flag, e.g.
>
> tflags DKIM_SIGNED net nice noautolearn
>
> Note that there is no way to set or clear a single flag; you have to list all
> flags that should be set.
Thanks for the solution
>
> --
> Magnus Holmgren [EMAIL PROTECTED]
> (No Cc of list mail needed, thanks)
>
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`-.| Piavlo `.
\, Alexander \)
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