On 4/29/06, List Mail User <[EMAIL PROTECTED]> wrote:
While SA is quite robust largely because of the design feature that
no single reason/cause/rule should by itself mark a message as spam, I have
to guess that the FP rate that the majority of users see for BAYES_99 is far
below 1%.
Anyway, to better address the OP's questions: The system is more
robust if instead of changing the weighting of existing rules (assuming that
they were correctly established to begin with), you add more possible inputs
Exactly. For example, I find that anything in the subset consisting
of messages that don't mention my email address anywhere in the To/Cc
headers and also scoring above BAYES_70 has close to 100% likelyhood
of being spam. However, since I also get quite a lot of mail that
doesn't fall into that subset, I can't simply increase the scores for
the BAYES rules.
In this case I use procmail to examine the headers after SA has scored
the message, but I've been considering creating a meta-rule of some
kind. Trouble is, SA doesn't know what "my email address" means (it'd
need to be a list of addresses), and I'm reluctant to turn on
allow_user_rules.
