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 <h.rei...@thelounge.net
<mailto:h.rei...@thelounge.net>> 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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