> ... Do you train *both*, spam *and* ham? Any chance these
> have been trained incorrectly before? What Bayes score do they actually
> get? The X-Spam-Status header would be sufficient to see.
>
> The few lines of 'sa-learn --dump magic' would be good, too. Oh, and you
> are training Bayes as the same user SA checks the mail for, right?
Yes, i trained both. By the way, i use spamassassin with amavis.
This is my bayes result:
~# sa-learn --dbpath /var/lib/amavis/.spamassassin/bayes --dump magic
0.000 0 3 0 non-token data: bayes db version
0.000 0 3270 0 non-token data: nspam
0.000 0 8809 0 non-token data: nham
0.000 0 120576 0 non-token data: ntokens
0.000 0 1279001124 0 non-token data: oldest atime
0.000 0 1284660563 0 non-token data: newest atime
0.000 0 1284653885 0 non-token data: last journal sync
atime
0.000 0 1284615337 0 non-token data: last expiry atime
0.000 0 0 0 non-token data: last expire atime
delta
0.000 0 0 0 non-token data: last expire
reduction count
I know, that just some blacklisted words are really not the solution. So i
put the threshold of spam lower in amavis conf:
$sa_tag_level_deflt = undef;
$sa_tag2_level_deflt = 6.31;
$sa_kill_level_deflt = 15;
$sa_dsn_cutoff_level = 25;
A typical score of a "Uhren"-mail is:
X-Virus-Scanned: Debian amavisd-new at ew6.org
X-Amavis-Alert: BAD HEADER, Duplicate header field: "Cc"
X-Spam-Flag: NO
X-Spam-Score: 12.989
X-Spam-Level: ************
X-Spam-Status: No, score=12.989 required=15 tests=[BAYES_99=3.5,
DNS_FROM_OPENWHOIS=1.13, HTML_MESSAGE=0.001, PYZOR_CHECK=3.7,
RCVD_IN_PBL=0.905, RCVD_IN_SORBS_HTTP=0.001, RCVD_IN_SORBS_WEB=0.619,
RCVD_IN_XBL=3.033, RDNS_NONE=0.1]
So with "$sa_tag2_level_deflt = 6.31" it is ok. Before i had 15. Above 6.31
the mails are directly put to the Spam-folder, so with IMAP, the user can
still look at them.
Anyway, do you think i need to update to 3.3.x or is 3.2 still OK?
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