Re: [opensuse] Kmail & Spamassassin
- From: "John Andersen" <jsamyth@xxxxxxxxx>
- Date: Mon, 31 Mar 2008 09:48:15 -0700
On Mon, Mar 31, 2008 at 9:30 AM, Kaare Rasmussen <kaare@xxxxxxxxxx> wrote:
I've recently installed the Spamassassin filter for Kmail. It sure removes
some spam, but not nearly enough. Typycally it will remove approximately 75
out of 175 spam messages, leaving 100 left for me to sift through.
I've let it learn what is spam for a week or so now, with absolutely no impact
on the ratio. Obviously, I wonder if I register spam in vain, did I forget
something, do I have to few messages (don't know how to see the numbers, but
I guess I have 1-2.000 spam messages registered), or is it not that efficient
to have identified spam as I thought?
Let it learn? Or teach it?
The keys to SA is get razor working.
All the network tests are useful, but if razor says its spam it is, period.
Then make sure you understand how bayes databases have to be set up.
Since SA does not block spam, merely tags it, you have to add kmail filters
to move the probably spam to a folder that you inspect occasionally.
Set SA to record tests that it hit upon, and not to mess with the subject.
Then look at stuff it says is not spam (but which really is) and see
which rules are fireing. If bayes_99 is not hitting then you have
your bayes set up wrong, or its still not trained properly.
You have to explicitly tell it which is spam and which is ham for a
while. The easiest way to do this is to create a folder called
MissedSpam and one called FalseSpam (or some such) and
move/copy miss-categorized messages into those folders.
Then use sa-learn to pass those mailboxes to the learning
process to train bayes, and (if you register) report them to
Razor.
Without this, SA won't be anywhere near as effective as
it can be.
I get less than 1 spam per day using SA, and never the
same spam twice.
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- [opensuse] Kmail & Spamassassin
- From: Kaare Rasmussen
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