On Fri, 8 Nov 2013, Sergio Durigan Junior wrote:
On Friday, November 08 2013, John Hardin wrote:
On Fri, 8 Nov 2013, Sergio Durigan Junior wrote:
#> spamc -c < spam.file
0.0/5.0
#> spamc -L spam < spam.file
(successful message saying that the spam was learned)
#> spamc -c < spam.file
0.0/5.0
I have already updated my Bayesian database, restarted the spamd
service, etc. I was expecting that I'd get a high rate after feeding
the spam to SpamAssassin, but that's not happening. Any suggestions?
Try using sa-learn to train Bayes.
I don't think sa-learn can help with spamd. Its own manpage mention
that, for spamd users, "spamc -L" is the way to go.
Not true. sa-learn is just fine for spamd with a global Bayes database,
and it's recommended for administrative simplicity if you have that
environment.
The big thing to keep in mind is that the user running the training
needs to be the same user that spamd is running as; if not, depending
on your bayes database config, you may be training a different Bayes
database than the one spamd is reading.
Hm, really? I thought spamd kept a global Bayes database, and that
everyone calling "spamc -L" would end up feeding this database, and not
some local one.
Global vs. per-user Bayes databases is a site-specific config. However, it
should be consistent - spamd should be reading from and training to the
bayes database of the user running spamc, so I don't off the top of my
head know why it dosn't appear to be working for you.
What are the Bayes database statistics before and after running spamc -L?
(sa-learn --dump magic)
I use a global database and sa-learn, so I don't have any direct
experience with spamc -L quirks, sorry. That's why I suggested sa-learn.
--
John Hardin KA7OHZ http://www.impsec.org/~jhardin/
jhar...@impsec.org FALaholic #11174 pgpk -a jhar...@impsec.org
key: 0xB8732E79 -- 2D8C 34F4 6411 F507 136C AF76 D822 E6E6 B873 2E79
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