On 9/27/2024 04:05:51, Matus UHLAR - fantomas wrote:
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.
You some "don't because" examples? Seems to me, off hand, that if it's
99% or 99.9% then a high value does no harm. Perhaps half what I have
would be sufficient though.
* -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.
Can you expand on that a bit? Did not know there was such an item. Is
it obvious in the documentation?
