Re: Train Spamassassin

Okay, i did an export from my Junk folder with a Thunderbird Plugin, it 
worked quiet well.

But at least that is not a very nice way! Does someone know a good 
script that pulls a folder from imap in a sa-learn compatible format?

Thoses 2 do not work, sa-learn could not encode them:

https://github.com/rtucker/imap2maildir

https://github.com/rcarmo/imapbackup



Am 05.01.17 um 04:50 schrieb Reindl Harald:
>
>
> Am 05.01.2017 um 03:10 schrieb Ryan Butler:
>> There's also a dbmail-export command isn't there to turn it into mbox 
>> files?
>
> yes, but you need to fix your picture how to train SA *properly*
>
> blowing each and every email there without 100% classification is the 
> wrong way - every single missclassified message does that much harm 
> that you need 10-20 correct ones fixing the damage
>
>> On Wed, Jan 4, 2017 at 5:21 PM, Reindl Harald <[email protected]
>> <mailto:[email protected]>> wrote:
>>
>>
>>
>>     Am 04.01.2017 um 22:32 schrieb Claas Kähler:
>>
>>         Okay this part is easy, but how could i extract samples from
>>         dbmail to
>>         put them into a folder?
>>
>>
>>     by IMAP - you are not supposed to directyl access email via mysql
>>     since you underestimate the complexity of the strcuture and must not
>>     rely on internal aka non-public API's
>>
>>         Am 04.01.17 um 22:26 schrieb Reindl Harald:
>>
>>
>>
>>             Am 04.01.2017 um 20:50 schrieb Claas Kähler:
>>
>>                 Hallo everybody,
>>
>>                 I have a serious Spam-Problem and I want to feed
>>                 sa-learn with those
>>                 Spam-mails to get rid of it.
>>
>>                 Has someone found a solution to train Spamassassin with
>>                 data from
>>                 DBMail?
>>
>>
>>             just put your samples in folders and use "sa-learn" with the
>>             correct user
>>
>>
>>             [root@mail-gw:~]$ bayes-stats.sh
>>             0      81476    SPAM
>>             0      25659    HAM
>>             0    3227434    TOKEN
>>
>>             insgesamt 376M
>>              24K -rw-r----- 1 sa-milt sa-milt  24K 2017-01-04 16:29
>>             bayes_seen
>>              65M -rw-r----- 1 sa-milt sa-milt  81M 2017-01-04 16:29
>>             bayes_toks
>>             312M -rw-r----- 1 sa-milt sa-milt 312M 2017-01-04 16:29
>>             wordlist.db
>>
>>             BAYES_00         1682   58.99 %
>>             BAYES_05           84    2.94 %
>>             BAYES_20           81    2.84 %
>>             BAYES_40          104    3.64 %
>>             BAYES_50          394   13.81 %
>>             BAYES_60           56    1.96 %     9.75 % (OF TOTAL 
>> BLOCKED)
>>             BAYES_80           60    2.10 %    10.45 % (OF TOTAL 
>> BLOCKED)
>>             BAYES_95           38    1.33 %     6.62 % (OF TOTAL 
>> BLOCKED)
>>             BAYES_99          352   12.34 %    61.32 % (OF TOTAL 
>> BLOCKED)
>>             BAYES_999         285    9.99 %    49.65 % (OF TOTAL 
>> BLOCKED)
>>
>>             DELIVERED        5104   91.91 %
>>             DNSWL            4984   89.75 %
>>             SPF              4088   73.61 %
>>             SPF/DKIM WL      2250   40.51 %
>>             SHORTCIRCUIT     2690   48.44 %
>>
>>             BLOCKED           574   10.33 %
>>             SPAMMY            506    9.11 %    88.15 % (OF TOTAL 
>> BLOCKED)
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