> Benny Pedersen wrote:
>>
>>
>> On Sun, July 26, 2009 15:29, snowweb wrote:
>>
>>> 0.000 0 258 0 non-token data:
>>> nspam
>>> 0.000 0 160 0 non-token data:
>>> nham
>>
>> try to have them more or less equal to have good bayes db
>>
>> so if less then 1000 in diff is fine
>>
>> if more then 1000 adjust learning scores
>>
>>> I see from that, that I've not trained as many HAM as I
>>> thought! OK, I'm off
>>> in search of some more HAM! Thanks guys.
>>
>> super you found the problem finaly
>>
>> --
>> xpoint
>>
>
> Sorry, it hasn't solved it :(
>
> As you can see below, I now have more than 200 of both
> SPAM & HAM trained:
>
> [r...@s1 Maildir]# sa-learn --dump magic
> [1644] warn: FuzzyOcr: Cannot find executable for
> tesseract
> 0.000 0 3 0 non-token data:
> bayes db version
> 0.000 0 278 0 non-token data:
> nspam
> 0.000 0 221 0 non-token data:
> nham
> 0.000 0 34120 0 non-token data:
> ntokens
> 0.000 0 1245088823 0 non-token data:
> oldest atime
> 0.000 0 1248616170 0 non-token data:
> newest atime
> 0.000 0 1248620830 0 non-token data:
> last journal sync atime
> 0.000 0 0 0 non-token data:
> last expiry atime
> 0.000 0 0 0 non-token data:
> last expire atime delta
> 0.000 0 0 0 non-token data:
> last expire reduction count
>
> but here are the spam headers of a message, which show
> that bayes is not being used:
>
> X-Spam-Flag: NO
> X-Spam-Checker-Version: SpamAssassin 3.2.4 (2008-01-01)
> on s1.snowweb.info X-Spam-Level: ******
> X-Spam-Status: No, score=3.0 required=4.7
> tests=RELAYCOUNTRY_US autolearn=no version=3.2.4
> X-Spam-Report:
> * 3.0 RELAYCOUNTRY_US Relayed through United States
> of America
> * 0.0 HTML_MESSAGE BODY: HTML included in message
> X-Spam-Relay-Country: US US US US US US US US US
>
> This is not a random event. Bayes is not being used for
> any message.
Which user you run the spam check with? sa-learn shows root's magic. If use for
example use user spam to check the spam, you should call sa-learn as
sa-learn -u spam --dump magic
