Am 05.01.2017 um 12:56 schrieb Claas Kähler:
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?
a plugin?just "save as" - the eml files *are* sa-learn compatible by definition because they are nothing else than a raw-message in mbox format
Thoses 2 do not work, sa-learn could not encode them: https://github.com/rtucker/imap2maildir https://github.com/rcarmo/imapbackup
see attachmentthe trainig-scripts itself are not included, it just pulls samples and talks to spamd to ignore junk which is already classified as BAYES_99
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 damageOn 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)_______________________________________________ DBmail mailing list DBmail@dbmail.org http://lists.nfg.nl/mailman/listinfo/dbmail_______________________________________________ DBmail mailing list DBmail@dbmail.org http://lists.nfg.nl/mailman/listinfo/dbmail
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<<attachment: spamfilter-fetch-samples.php>>
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