Justin Mason schrieb:
martin f krafft writes:
Hi list,
I just had a flood of spam coming through, which SA classified as
ham. On closer inspection, it turns out that the only tests
triggered for all those mails were HTML_MESSAGE and BAYES_99.
HTML messages are commonplace today (unfortunately), so they don't
add anything to the score.
BAYES_99 yields 3.5 points.
What's curious is that in this scenario, even though SA thinks that
the message is 99%-100% likely to be spam, it will always classify
it as ham, and further learning does not have any noticeable effect.
I know how SA scores are computed. I do wonder how that algorithm
applies to the BAYES_* tests though. Don't you think BAYES_99 should
yield > 5 points to trigger the threshold on default installs?
Shouldn't thus BAYES_* be renormalised?
The Bayes rules are too dependent on user training to be entirely
trustworthy, and most users will not train them enough, or occasionally
make mistakes, for them to be treated as such. However, if you've put in
the effort to train them well, feel free to increase their score...
Yes, most users wont train, but constantly complain about the bad
performance of spam scoring ;-).
Never seen False Scoring for BAYES_99 (well trained, manual).
Spam rarely gets > BAYES_50.
So the higher score works fine (for me).
Just my 2 cent.
--j.
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Grüsse/Greetings
MH
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