http://plg.uwaterloo.ca/~gvcormac/spamcormack1.pdf
This study is much better than most analysis of different spam filters,
in that it deals with SpamAssassin in different modes of Bayesian
learning, and cares about false positives as well as false negatives.
However, it's needlessly obscure in it's terminology and statistics.
The critical summary info is on page 14 in tables VIII (ham
misclassification, by which he means false positives) & IX (spam
misclassification, by which he means false negatives).
Not surprisingly, SpamAssassin Bayes supervised (i.e., mistake-based
training) works best.
- dan
--
Dan Kohn <mailto:[EMAIL PROTECTED]>
<http://www.dankohn.com/> <tel:+1-650-327-2600>
-----Original Message-----
From: Tony Finch [mailto:[EMAIL PROTECTED] On Behalf Of Tony Finch
Sent: Thursday, July 15, 2004 03:26
To: [EMAIL PROTECTED]
Subject: paper comparing spam classifiers
Someone recently posted a URL to one of the SA mailing lists pointing to
a
paper which did an extremely thorough comparison of the leading
open-source statistical spam classifiers. Can someone remind me of it
please? I've lost the link.
Tony.
--
f.a.n.finch <[EMAIL PROTECTED]> http://dotat.at/
FAEROES: WEST OR SOUTHWEST BACKING SOUTH 3 OR 4. SHOWERS. MODERATE OR
GOOD.
