On Tue, Mar 07, 2006 at 08:44:59PM -0500, Gabriel M. Wachman wrote:
> > The perceptron (form of neural net used  in SA 3.0.0 and higher) is used by 
> > the
> > developers to generate the scores prior to release. 99.9% of end-users do 
> > not
> > ever use the perceptron.
> > 
> By "do not use" do you mean that it is completely ignored during
> classification, or that only the fixed pre-trained neural net is used

The output from the perceptron are scores (weights) which are used during
classification.  As Matt said, users tend not to generate their own scores,
and so therefore don't run the perceptron, they just use the output from when
it's run pre-release.

> and the end-user does not change it? If it's not used at all, why does
> the FAQ state, "In SpamAssassin 3.x, the scores are assigned using a
> neural network trained with error back propagation?"

Because the scores are assigned by the perceptron.  Your confusion seems to be
related to how SpamAssassin works in general:

A mail is sent to SpamAssassin through some means (spamassassin, spamc/spamd,
third-party tool, etc.)  SpamAssassin reads in all of the config files,
including the scores (as generated by the perceptron), and runs all of the
rules over the message.  At the end, the scores for all rules that matched are
summed and the result is used to determine ham vs spam (by default if the
score is >= 5, the message is considered spam).

Hopefully this helps.

> Let me make sure I understand: the Bayes database is the primary form of
> customization done by default, although the underlying pre-trained
> neural net is the primary method for weighting scores? If you just run
> spamassassin with the default settings, is it not using the neural net
> to weight the various test scores? Or is the neural net itself its own
> separate test?

The neural net (perceptron) generates the default scores.  The Bayes database
is used by the BAYES_* rules to determine statistically if the message content
is spam or not.

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