>> 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
One can also use
bayes_sql_override_username spam
in local.cf, if the bayes is in a SQL database. I have that, and there seems to
be no difference if I use -u or not.
