<html>
<head>
<meta http-equiv="content-type" content="text/html; charset=utf-8">
</head>
<body style="background-color: rgb(255, 255, 255); color: rgb(0, 0,
0); font-family: Palatino Linotype; font-size: 13px;"
bgcolor="#FFFFFF" text="#000000">
<p><tt>Hello, </tt><tt><br>
</tt></p>
<p><tt>After relatively long training of bayes filters, we are
consistently getting bayes99 score of 3.5 (on spam mails). </tt><tt><br>
</tt></p>
<p><tt>It seems this is the max score assigned to bayes99. How/where
can we increase this value? </tt><tt><br>
</tt></p>
<p><tt>Config files are at: /etc/amavisd.conf and at
/etc/mail/spamassassin/local.cf</tt><tt><br>
</tt></p>
<p><tt>Spam mails still get through because a higher total score is
needed for them to be auto designated as spam. </tt><tt><br>
</tt></p>
<p><tt>Here is a typical header of such a mail: </tt><tt><br>
</tt></p>
<blockquote>
<p><tt>X-Spam-Flag: NO</tt><tt><br>
</tt><tt>X-Spam-Score: 5.153</tt><tt><br>
</tt><tt>X-Spam-Level: *****</tt><tt><br>
</tt><tt>X-Spam-Status: No, score=5.153 tagged_above=-999
required=5.5</tt><tt><br>
</tt><tt> tests=[BAYES_99=3.5, BAYES_999=0.2,
DATE_IN_PAST_12_24=1.049,</tt><tt><br>
</tt><tt> DKIM_ADSP_CUSTOM_MED=0.001, FREEMAIL_FROM=0.001,</tt><tt><br>
</tt><tt> HTML_IMAGE_RATIO_06=0.001, HTML_MESSAGE=0.001,
IP_LINK_PLUS=0.012,</tt><tt><br>
</tt><tt> NML_ADSP_CUSTOM_MED=0.9, NORMAL_HTTP_TO_IP=0.001,</tt><tt><br>
</tt><tt> RP_MATCHES_RCVD=-0.313, SPF_HELO_PASS=-0.1,
SPF_PASS=-0.1]</tt><tt><br>
</tt><tt> autolearn=disabled</tt><tt><br>
</tt></p>
</blockquote>
<p><tt>How should I best handle the issue? I think that raising max
score from 3.5 to e.g. 6.0 might do the trick. Any other
options?<br>
</tt></p>
<p><tt>Some additional data: <br>
</tt></p>
<p><tt>$ sa-learn --dbpath '/var/amavis/var/.spamassassin' --dump
magic<br>
0.000 0 3 0 non-token data: bayes db
version<br>
0.000 0 2063 0 non-token data: nspam<br>
0.000 0 1010 0 non-token data: nham<br>
0.000 0 217776 0 non-token data: ntokens<br>
0.000 0 1219096335 0 non-token data: oldest
atime<br>
0.000 0 1476418883 0 non-token data: newest
atime<br>
0.000 0 1476418900 0 non-token data: last
journal sync atime<br>
0.000 0 1471602636 0 non-token data: last
expiry atime<br>
0.000 0 0 0 non-token data: last
expire atime delta<br>
0.000 0 0 0 non-token data: last
expire reduction count</tt></p>
<p><tt>Please advise.</tt></p>
<p><tt>Thanks in advance,<br>
Nick</tt><tt><br>
</tt></p>
</body>
</html>