On 08/11/03 01:57 PM, Hannu Liljemark sat at the `puter and typed:
> On Sat, Aug 09, 2003 at 04:25:00PM +0300, Louis LeBlanc wrote:
> 
> > I have attached a few of them here.  If anyone has any suggestions,
> > I'm more than happy to hear them.
> 
> If I were you, I'd train the Bayes classifier with these mails that
> sneaked past. Most seem to score in BAYES_30 range in your current
> environment, but with some training I'm willing to bet you'll see
> BAYES_90 for the same mails.

Always.  Every day, I archive the spam folder of all the messages
received the previous day.  At just past midnight, I run a script that
pulls down the spam folder from my server and uses it to train the
bayes filter - using the --forget switch so that these messages won't
be skipped if they were inadvertently learned as ham.  The script also
pulls down the Inbox and trains the filter on real email.

> Other things to consider would be Razor, DCC or Pyzor. Here most of
> the spammails you attached can be found from Razor's DB. I don't use
> others so can't say what DCC or Pyzor would say. Also RBL testing
> wouldn't hurt, as all those sample spams came from known open
> proxies.

I use Razor and whatever else SA checks by default.  Though I often
see messages that were flagged as probably spam by one DSBL or
another, but still fall under the 5.0 mark.

Thanks for the reply.

Lou
-- 
Louis LeBlanc               [EMAIL PROTECTED]
Fully Funded Hobbyist, KeySlapper Extrordinaire :)
http://www.keyslapper.org                     ԿԬ

Theory of Selective Supervision:
  The one time in the day that you lean back and relax is
  the one time the boss walks through the office.


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