On Thu, 9 Aug 2018 13:35:21 +0200
Matus UHLAR - fantomas wrote:
> >On 08/08/2018 15:04, Matus UHLAR - fantomas wrote:
> >>...of last 40 mail in my spambox, 14 matches MAILING_LIST_MULTI
> >>...of last 100 mail in spambox, 27 matches MAILING_LIST_MULTI
>
> On 09.08.18 08:54, Daniele Duca wrote:
> >I practically zeroed MAILING_LIST_MULTI the day it came in the
> >ruleset.
MAILING_LIST_MULTI has the default "nice" score of -1.0 rather than an
explicit score. I'm wondering if this is deliberate.
> >>but not possible to put:
> >>
> >>tflags BAYES_99 learn dothefuckingautolearn
>
> >Wouldn't
> >
> >tflags BAYES_99 autolearn_force
> >
> >do what you want? Or did I misunderstood completely what you meant?
I think you have probably misunderstood autolearn_force. All it does is
turn-off the check that requires that at least 3 points come from both
body and header rules when autolearning as spam.
> >Personally I'll never trust BAYES_* with autolearn_force. I saw some
> >FPs sometimes and I fear that autolearning would quickly lead to
> >poisoning
I would advise against using auto-training where it's possible to
train manually. It's not just a matter of mistraining, autolearning may
also bias the database in favour of types of spam that are easily
caught, thereby diluting the frequencies of tokens needed to catch the
difficult spam.
> with autolearn_force yes, it could apparently lead to poisoning.
>
> However, if "learn" only did its job (whatever it is) and only
> "noautolearn" would ignore the score, it would be just enough.
>
> Currently, as docs say, "learn" in fact implicates "noautolearn".
As does userconf.
> I just don't understand why. Simply use both flags and that's it.
If you really must do this just create a new rule without tflags and
then score it something like this:
3.0 3.0 0.001 0.001
i.e so it's scored in the non-Bayes score sets. You can just modify
the scores and tflags of an original rule, but that's less flexible.
