On 2021-04-22 02:31 PM, Matus UHLAR - fantomas wrote:
On 22.04.21 14:21, Steve Dondley wrote:
pts rule name              description
---- ---------------------- -------------------------------------------------- -0.0 RCVD_IN_DNSWL_NONE RBL: Sender listed at https://www.dnswl.org/,
                            no trust
                           [209.85.210.44 listed in list.dnswl.org]
-1.0 BAYES_00               BODY: Bayes spam probability is 0 to 1%
                           [score: 0.0000]
-0.0 SPF_PASS               SPF: sender matches SPF record
0.2 FREEMAIL_ENVFROM_END_DIGIT Envelope-from freemail username ends
                           in digit
                           [margaretkelly866[at]gmail.com]
0.0 FREEMAIL_FROM Sender email is commonly abused enduser mail
                           provider
                           [margaretkelly866[at]gmail.com]
0.0 SPF_HELO_NONE          SPF: HELO does not publish an SPF Record
-0.0 RCVD_IN_MSPIKE_H3      RBL: Good reputation (+3)
                           [209.85.210.44 listed in wl.mailspike.net]
0.0 HTML_MESSAGE           BODY: HTML included in message
-0.1 DKIM_VALID_EF Message has a valid DKIM or DK signature from
                           envelope-from domain
0.1 DKIM_SIGNED Message has a DKIM or DK signature, not necessarily
                           valid
-0.1 DKIM_VALID_AU Message has a valid DKIM or DK signature from
                           author\'s domain
-0.1 DKIM_VALID Message has at least one valid DKIM or DK signature
-0.0 RCVD_IN_MSPIKE_WL      Mailspike good senders

This email is bit of an outlier as most of these emails will get flagged with bayes_99 and bayes_999 but this one actually gives it bayes_00.

My bayes filter has been trained with about 2000 examples of spam and ham.

now, train as needed - this one as spam.

OK, so I fixed my configuration issue. So now the bayes filtering is working when I flag an email as spam in my mail client:

Content analysis details:   (4.5 points, 5.0 required)

 pts rule name              description
---- ---------------------- --------------------------------------------------
<snip>
 1.0 BAYES_999              BODY: Bayes spam probability is 99.9 to 100%
                            [score: 1.0000]
 3.5 BAYES_99               BODY: Bayes spam probability is 99 to 100%
                            [score: 1.0000]
<snip>

But as you can see, the email is still not hitting the 5.0 threshold.

I could add another point between BAYES_999 and BAYES_99 scores but that seems reactionary. Is there a better way? Should I thrown in another point for certain keywords in marketing emails like these?

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