>>  I beg to differ with you.  On the contrary, there have been a number
>>of recent posts to the SA list from admins all of whose spam is now
>>identified as BAYES_00 and AWL, because they enabled autolearn and let
>>it run on its own while a lot of spam was slipping through.
>>    
>>
>
>This was my issue and the reason I turned off Bayes and DSPAM, because of 
>our lack of spending the time manually training it and leaving it on 
>autolearn, it was causing more harm than good.  We have a large user base, 
>5K+ users in different states/countries, it was not clear cut to implement 
>a user mechanism where they could manually flag email as spam or ham and 
>train the DB, additionally we use Notes on the back end.
>
>
>  
>
>>  If significant amounts of spam are being missed in the first place,
>>they are ipso facto being scored low, so if you aren't *manually*
>>training them as spam they are more likely to get learned as ham than
>>as spam.
>>
>>    
>>

We do not use AWL; this has proven  to be dangerous. We use dspam and 
Bayes in parallel, train Bayes with hamp/spam levels of 0.0 and 5.0 and 
score both with 3.5 on spam and -1.0  on nonspam. In conjunction with 
the "postfix mini-greylister" aka
reject_unverified_sender and some other sanity rule on the domain name, 
mx etc. we have very rare cases of spam slipping through with no manual 
intervention. We are rejecting about 95 % of mail so it's not because we 
dont't get spam....
But I agree mileages might vary widely. The last argument might be true 
but in practice I found we catch most things because at least dspam 
starts to score mails when several similar ones have arrived and with 
that score bayes will soon start to score too.

Yours,
Jakob Curdes


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