Quoting RW <rwmailli...@googlemail.com>:
On Fri, 31 Jul 2009 03:55:48 +0200
Karsten Bräckelmann <guent...@rudersport.de> wrote:
The default of 0.1. It's a default for a reason.
But that *really* is not your problem. Your problem is with learning
spam, not learning even more ham. Just as you mentioned in your
original report. See my previous response for a solution. You want to
learn more spam.
What he actually wrote was that 3.7% of _all_messages_ were hitting
hitting BAYES_00, and 1.7% were hitting BAYES_99.
If he actually meant what he wrote and doesn't have an extraordinary
spam/ham ratio, then he clearly has a problem with both spam and
ham.
I cleared my maia statistics a couple of days ago. Since then
BAYES_00 has triggered 4510 times, BAYES_99 2366 times and BAYES_50
1568 (all the other BAYES_XX are less then 1000 times). In those same
couple of days we have processed about 45,000 messages (this is the
number of messages that actually reached spamassasin and wasn't out
right rejected). So my initial percentages were way off (I was going
by maia mailguards sa rule statistics). So roughly 10% of mail is
hitting BAYES_00 and 5% is hitting BAYES_99. It seems to me that
BAYES_99 should probably be triggered more often then BAYES_00.
If there is a better way to get sa statistics I'd be happy to know.
I know that the bayes success rate comes down to training, but like
every other administrator I can't possible check every message for
accuracy and I was hoping to make the auto learn a little better. I
thought maybe I just didn't have enough rules (both negative and
positive scoring) to trigger the auto learn often enough.
Thanks,
--Dennis
