On 2004-06-30 Ben Giddings <bg-exim@???> wrote:
[...]
> warn message = X-Spam-Score: $spam_score ($spam_bar)
> spam = mail:true
> warn message = X-Spam-Flag: YES
> spam = mail
> warn message = X-Spam-Report: $spam_report
> spam = mail
> deny message = Spammy message detected
> spam = mail:true
> condition = ${if >{$spam_score_int}{150}{1}{0}}
[...]
> I used to have SpamAssassin set with report_safe set to 1, which would
> create a new message with the report and add the other one as an
> attachment, but I understand that doesn't work with the exiscan patch?
Correct. exiscan only checks sa's diagnosis, it does not keep its
modifcations to the message. (I think sa-exim can.)
> Anyhow, my question is this:
> If I take these modified messages and try to use sa-learn to train my
> bayesian filters, will the fact these have modified headers, including
> te spam report skew the bayesian algorithm?
[...]
Mail::SpamAssassin::Conf(3pm)
bayes_ignore_header header_name
If you receive mail filtered by upstream mail systems, like a
spam-filtering ISP or mailing list, and that service adds new
headers (as most of them do), these headers may provide
inappropriate cues to the Bayesian classifier, allowing it to take
a "short cut". To avoid this, list the headers using this setting.
Example:
bayes_ignore_header X-Upstream-Spamfilter
bayes_ignore_header X-Upstream-SomethingElse
cu andreas
--
"See, I told you they'd listen to Reason," [SPOILER] Svfurlr fnlf,
fuhggvat qbja gur juveyvat tha.
Neal Stephenson in "Snow Crash"
