On Mon May 8 2006 6:58 pm, Frank Cox wrote:
Has anyone used this?
It looks very cool. Are there any up-to-date rpm packages around anywhere?
The only ones that I could find are substantially out-of-date.
I've used Spambayes on both Linux and Windows boxes for over a year now. It's
a normal part of my installation of a new distro, these days. Spambayes can
be detected by Kmail's anti-spam configuration wizard these days, and that's
Installation is extremely simple. Unpack the tarball anywhere you prefer, and
run 'python set_up.py' as root from the folder in which you unpacked the
tarball - that installs everything (you can delete the folder after that).
Then, you want to start it at boot-time. I use
'nohup python /usr/bin/sb_server.py &'
as a line in rc.local, or better, lately I've been using the above as a script
file in my /.kde/startup folder - that invokes the spambayes server as user
instead of root - it works just fine that way.
Then, either reboot, or start the spambayes server manually and open Firefox
or any browser and put 'http://localhost:8880/' in your address bar and click
on 'configure' - I usually just worry about the topmost two fields, leaving
everything else in default.
In the topmost field, you enter the url of your pop mail servers, separated by
commas. In the ports field, just pick random ports to proxy on, separated by
commas ( I use 1110,1111,1112, for example)
After that, you have to configure your email client to use localhost for each
pop server, and the corresponding port you entered in the second field,
Spambayes should start piping your mail through its filters after that, if
you've got everything right. It will add a classification line to each mail
header, labeling it as 'spam', 'unsure', or 'ham' (look at your header lines,
and you'll this extra line as
- use your email client filters to direct the mail to wherever you'd like it
to end up according to these classifications. If you use kmail, as already
mentioned, much of the email client header classification filtering gets done
for you if you go through the anti-spam wizard...
Hope that helps - there's more that can be configured, and I may have left
something out, but that should be enough to get you going. You'll have to
read the faq on the spambayes site to learn about training, but that's fairly
straightforward. After several days, you'll find Spambayes removing well over
90% of your spam with almost no false positives. I get over 400 spams per day
because of multiple published email addresses, but, Spambayes makes that
completely manageable. One further comment, while it's true that Thunderbird
uses bayesian filtering, and it's pretty good, it's not the same as
Spambayes, which in my opinion is an even better implementation of bayesian
principles - there are some pretty good docs on the net if you google for
them, to explain the principles behind bayesian filtering - Spambayes is one
of several implementations of the principles involved.