Are there other criteria, though?

For example, I have set the threshold at which Auto-Learn is "triggered" for
Spam at 7.99. Anything scoring over that is designated to be "auto-learned."

Yet one came through this morning at 12.9, and it did NOT "auto-learn."

However, Bayesian probability was something like 0.997, so I thought "maybe
at that level it figures it doesn't need to "auto-learn" this one. But when
I "hand-feed" it through SA-Learn, it accepts it!

So what's the critical difference here? I really want to stop even looking
at or in any way dealing with my Spam corpus any more. I want to simply toss
anything that is marked as Spam, AFTER it has been "auto-learned". I'm not
getting any false-positives any more (and darned few false-negatives). I'm
ready to just not worry about it.

But I'm afraid that without satisfactory "auto-learn" performance I'm going
to veer off course over time.

I've yet to see any Spam that has been "auto-learned," after searching
diligently for a few days. Ham "auto-learn" seems to work just fine, but not
Spam.

William L. Polhemus, Jr. P.E.
Polhemus Engineering Company
Katy, Texas USA

-----Original Message-----
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Martin
Radford
Sent: Tuesday, October 28, 2003 2:23 PM
To: Bill Polhemus
Cc: [EMAIL PROTECTED]
Subject: Re: [SAtalk] Auto-Learn

At Tue Oct 28 18:13:03 2003, Bill Polhemus wrote:

> How can I know for sure if Auto-Learn is functioning correctly?

Auto-learning is by definition automated, and as such there's a risk
that messages will be learned as the wrong type.  Learning ham as spam
(or vice-versa) can seriously damage the reliability of the bayesian
database.  To avoid this, there's a significant range in which
autolearning is disabled.

"autolearn=no" indicates that this particular message was not learned
from, not that autolearning as a whole is switched off.




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