<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN">
<HTML><HEAD>
<META http-equiv=Content-Type content="text/html; charset=us-ascii">
<META content="MSHTML 6.00.6000.16587" name=GENERATOR></HEAD>
<BODY>
<DIV dir=ltr align=left><SPAN class=617581414-21022008><FONT face=Arial
color=#0000ff size=2>A few possibilities immediately occur to me; there may
be others.</FONT></SPAN></DIV>
<DIV dir=ltr align=left><SPAN class=617581414-21022008><FONT face=Arial
color=#0000ff size=2></FONT></SPAN> </DIV>
<DIV dir=ltr align=left><SPAN class=617581414-21022008><FONT face=Arial
color=#0000ff size=2>The first is simply to keep training on the misclassified
messages. Sooner or later, you'll probably accumulate enough cues that SpamBayes
will classify the messages as you wish.</FONT></SPAN></DIV>
<DIV dir=ltr align=left><SPAN class=617581414-21022008><FONT face=Arial
color=#0000ff size=2></FONT></SPAN> </DIV>
<DIV dir=ltr align=left><SPAN class=617581414-21022008><FONT face=Arial
color=#0000ff size=2>The second is the first on steroids: discard your current
training data and train from scratch. It sounds drastic, but SpamBayes is easy
to train and learns quickly. You should be getting very good results by the time
you've trained on a few dozen messages.</FONT></SPAN></DIV>
<DIV dir=ltr align=left><SPAN class=617581414-21022008><FONT face=Arial
color=#0000ff size=2></FONT></SPAN> </DIV>
<DIV dir=ltr align=left><SPAN class=617581414-21022008><FONT face=Arial
color=#0000ff size=2>A third possibility is to use the SpamBayes Manager to
adjust the cutoff for possible spam. If SpamBayes is assigning the offending
messages a spam probability close to but above the cutoff, you could adjust the
cutoff upward slightly. For example, if SpamBayes typically assigns the messages
an 18% spam probability and the possible spam cutoff is 15%, you could adjust
the cutoff to 20%. The down side to this approach is that it will affect all
messages, and it's possible that you'll get more spam in your
inbox.</FONT></SPAN></DIV>
<DIV dir=ltr align=left><SPAN class=617581414-21022008><FONT face=Arial
color=#0000ff size=2></FONT></SPAN> </DIV>
<DIV dir=ltr align=left><SPAN class=617581414-21022008><FONT face=Arial
color=#0000ff size=2>And finally, there's the option of setting up an Outlook
rule to move messages from that particular sender to some "safe haven" folder
(that is, a folder that SpamBayes is not filtering). SpamBayes attempts to
process messages after any Outlook rules have run, so you should be able to
squirrel these messages away before SpamBayes classifies them. This is
potentially labor-intensive and fragile, and it's somewhat at odds with the good
work that SpamBayes is trying to do for you, so I'd make this a last
resort.</FONT></SPAN></DIV>
<DIV dir=ltr align=left><SPAN class=617581414-21022008><FONT face=Arial
color=#0000ff size=2></FONT></SPAN> </DIV>
<DIV dir=ltr align=left><SPAN class=617581414-21022008><FONT face=Arial
color=#0000ff size=2>If you find a solution that works for you, it would be a
kindness to reply to the list so that your solution will be part of the
searchable mailing list archive for future reference.</FONT></SPAN></DIV><BR>
<DIV class=OutlookMessageHeader lang=en-us dir=ltr align=left>
<HR tabIndex=-1>
<FONT face=Tahoma size=2><B>From:</B> spambayes-bounces@python.org
[mailto:spambayes-bounces@python.org] <B>On Behalf Of </B>Ted
Ressler<BR><B>Sent:</B> Thursday, February 21, 2008 9:04 AM<BR><B>To:</B>
spambayes@python.org<BR><B>Subject:</B> [Spambayes] unmarking
spam<BR></FONT><BR></DIV>
<DIV></DIV>
<DIV><SPAN class=703150114-21022008><FONT face=Arial size=2>I am using the
latest version of spambayes on windows xp. It works well except that it
continues to mark all email, with or without attachments from one particular
party as suspected spam. I always click, remove from spam, but every time
something comes in from that party it is marked as spam. What can I
do?</FONT></SPAN></DIV>
<DIV><SPAN class=703150114-21022008><FONT face=Arial
size=2></FONT></SPAN> </DIV>
<DIV><SPAN class=703150114-21022008><FONT face=Arial
size=2>Thanks</FONT></SPAN></DIV>
<DIV><SPAN class=703150114-21022008><FONT face=Arial
size=2>Ted</FONT></SPAN></DIV></BODY></HTML>