On 26.09.24 10:27, joe a wrote:
Maybe I should not ask this, but . . .
A relatively innocuous member informational email from a local town Library
(monthly) gets marked as spam as shown below.
The BAYES_99 and BAYES_999 values are something I am toying with for other
reasons. Seems odd these should hit either one of those tests.
So, on the one hand I can add them to whitelist and be done with it, or I can
add
them to missed HAM for re-learning.
Which is the best approach?
so far, both. You may need to relearn multiple their (monthly) mails before
it has effect.
X-Spam-Report:
* 4.1 BAYES_99 BODY: Bayes spam probability is 99 to 100%
* [score: 1.0000]
* 5.0 BAYES_999 BODY: Bayes spam probability is 99.9 to 100%
* [score: 1.0000]
You have raised BAYES_99 and BAYES_999 to huge values so I recommend to
rethink that.
* -0.1 DKIM_VALID Message has at least one valid DKIM or DK signature
* -0.1 DKIM_VALID_AU Message has a valid DKIM or DK signature from
* author's domain
you can safely welcomelist_from_dkim their mail address.
--
Matus UHLAR - fantomas, uh...@fantomas.sk ; http://www.fantomas.sk/
Warning: I wish NOT to receive e-mail advertising to this address.
Varovanie: na tuto adresu chcem NEDOSTAVAT akukolvek reklamnu postu.
99 percent of lawyers give the rest a bad name.
