[Spambayes] Improved comparison of classifier changes?

[Piers Haken]

(This came to me in a dream. No, really...)

When comparing two different classifier/tokenizer strategies, instead of
just comparing the numbers of false  negatives and positives, how about
comparing some function (product, sum, average,
some-more-appropriate-statistical-function?) of the spam probability of
all messages in each classification (spam, ham, false-positive,
false-negative)? This might give a slightly better indication of not
just the numbers of messages that were classified correctly/incorrectly,
but of how sure the classifier was when it made those decisions.

.. or was I just dreaming...?

Piers.