On Mon, 04 May 2009 22:38:00 +0200
Karsten Bräckelmann <guent...@rudersport.de> wrote:
> According to that description and bug 2865 comment 3, the word
> "strongly" seems to be key here. Not checked the code, but comment 3
> pretty much translates to an additional constraint, that the real
> result (using the Bayes score-set) as seen in the X-Spam headers must
> agree with the auto-learner result for the message to be learned.
There are two separate tests, the autolearn result must be consistent
with the overall classification, and not inconsistent with the bayes
scoring.
From AutoLearnThreshold.pm:
my $learner_said_ham_points = -1.0;
my $learner_said_spam_points = 1.0;
if ($isspam) {
my $required_body_points = 3;
my $required_head_points = 3;
if ($body_only_points < $required_body_points) {
dbg("learn: auto-learn? no: scored as spam but too few body points (".
$body_only_points." < ".$required_body_points.")");
return;
}
if ($head_only_points < $required_head_points) {
dbg("learn: auto-learn? no: scored as spam but too few head points (".
$head_only_points." < ".$required_head_points.")");
return;
}
if ($learned_points < $learner_said_ham_points) {
dbg("learn: auto-learn? no: scored as spam but learner indicated ham (".
$learned_points." < ".$learner_said_ham_points.")");
return;
}
if (!$scan->is_spam()) {
dbg("learn: auto-learn? no: scored as ham but autolearn wanted spam");
return;
}
} else {
