[Python-Dev] The first trustworthy <wink> GBayes results

[Neil Schemenauer]

Tim Peters wrote:
> Under Graham's scheme, send it on.  It doesn't have grey areas in a useful
> sense, becuase the scoring step only looks at a handful of extremes:
> extremes in, extremes out, and when it's wrong it's *spectacularly* wrong
> (e.g., the very rare (< 0.05%) false positives generally have "probabilties"
> exceeding 0.99, and a false negative often has a "probability" less then
> 0.01).

I noticed that as well.  When the classifier goes wrong it goes badly
wrong and using different thresholds would not help.  It seems that
increasing the number of discriminators doesn't really help either.  Too
bad because otherwise you could flag those messages for human
classification.

On the bright side, based on the number of mis-classified messages in my
corpus, it looks like a human would have a very hard time doing a better
job.  Perhaps all that is needed is a bypass mechanism for that small
fraction of non-spammers.  That way if their initial message is rejected
they would still have some way of getting through.

Erik Naggum made an interesting comment.  He said that spam should be
handled at the transport level.  Greg's work on doing filtering at SMTP
time accomplishes this and makes a lot of sense.  When a message is
rejected, the sending mail server is the one that has to deal with it.
In the case of spam, the sending server is often an open rely.  Letting
it handle the bounces is sweet justice. :-)

I bring this up because "STMP time filtering" makes a bypass mechanism
work much better.  With a system like TMDA, confirmation notices usually
generate double-bounces.  Instead, we could reject the message with a
5xx error that includes instructions on how to bypass the filter (e.g.
include a cookie in the body of the message).

  Neil