Re: Bayes filter marking everything as ham

[Reindl Harald]

Am 01.06.2016 um 02:04 schrieb Peter Carlson:

On 05/31/2016 04:27 PM, Reindl Harald wrote:

Am 31.05.2016 um 23:58 schrieb Peter Carlson:

    May 30 09:04:53 www amavis[16577]: (16577-03) Passed CLEAN
    {RelayedInbound}, <snip> Tests:
[BAYES_00=-1.9,RCVD_IN_MSPIKE_H2=-0.001,SPF_PASS=-0.001,URIBL_BLOCKED=0.001],

    autolearn=ham autolearn_force=no, autolearnscore=-0.001, 3992 ms

the next one with amavis and URIBL_BLOCKED
(http://uribl.com/refused.shtml) - i get tired of aksing for help hile
not doing basic homework

Wow...I could say the same...I get tired of doing homework and not
getting any help

sorry, but when here are just 4 rules in teh reporting header i expect from anybody running a mailserver looking what they mean - just because it takes the same time then whine on a mailing list

Amavias != pure SA

I never claimed it was.  Are you insinuating that somehow amavis is
causing  a BAYES_00 false negative?

finally that would likely have prevented ruin your bayes from the start

WTF - in your original post it was not clear that bayes is your problem because even with a BAYES_00 when you would follow basic best prctices like a recusrsion dns-cache on your inbound MX you would have a ton of RBL/URIBL likely catch the message and overrule BAYES_00 however, your major mistake (besides URIBL_BLACK) is running autolearning before you have a solid base (setup itself and hand classified messages)

URIBL_BLOCKED == read some basics

your reply == useless.  You have no idea what I may or may not have
read.  You are under no obligation to provide any help to me or anyone
else.  I suggest that if for whatever reason you find my question
offensive that instead of hitting reply, you simply hit delete.

My initial question still remains, why is BAYES_00 always at -1.9. Why
is it marking all messages as ham?

      0.000          0        642          0  non-token data: nspam
      0.000          0       9415          0  non-token data: nham

because some fool trains spam as ham (autolearning and wrong manual learning combined) what do you expect when you train 15 times more ham than spam and than have "autolearn=ham" enabled?

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