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To: "Craig R.Hughes" <craig@deersoft.com>
Cc: yyyy@spamassassin.taint.org (Justin Mason),
	"Malte S. Stretz" <msquadrat.nospamplease@gmx.net>,
	SpamAssassin Talk ML <spamassassin-talk@lists.sourceforge.net>
References: <B7973337-B468-11D6-9F04-00039396ECF2@deersoft.com>
From: Scott A Crosby <scrosby@cs.rice.edu>
Organization: Rice University
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Subject: [SAtalk] Re: results for giant mass-check (phew)
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X-Original-Date: 21 Aug 2002 06:57:35 -0500
Date: 21 Aug 2002 06:57:35 -0500

On Tue, 20 Aug 2002 11:14:50 -0700, Craig R.Hughes <craig@deersoft.com> writes:

> On Tuesday, August 20, 2002, at 07:23  AM, Justin Mason wrote:
> 
`> Remember that the GA is going to be considering combinatorial uses of
> the rules, so rules which look dodgy on their own might be gems for
> the GA -- perhaps something with a S/O ratio of .5 actually occurs
> often in combination with some other rule, and in those situations,
> helps to distinguish spam vs nonspam.
> 

We're currently using a perceptron classifier. It *can't* learn
combinations of rules.[1]

I gave an example, assume 4 rules:
   SPAM = (A or B) and (C or D)

It cannot learn that function.

A decision tree classifier *can* learn that example, and the function
above, where a .5 S/O rule is only important in certain
circumstances. (Then again, it may be smartest to hardcode a meta-rule
for that case, rather than trust to a naive DT learner.)

Scott


[1] To be fair, nor can a Bayes classifier.


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