| X-Spam-Status: No, hits=4.1 required=5.0 | tests=BAYES_90,NO_REAL_NAME | autolearn=ham version=2.55
auto_learn_threshold_nonspam is set to 1.9. Now I am wondering why on earth SpamAssassin learns that message as _ham_? As far as I can see, this should not happen.
The autolearn is NOT based on the final score of the email. The manpage details this quite clearly.
Auto learning is based on the score as if SA were run with bayes disabled. This includes changing which scoreset is used. This is done to prevent bayes from self-feeding. Also white/blacklist rules, and the AWL is
not used.
From the manpage Mail::SpamAssassin::Conf of version 2.54 -------------
auto_learn ( 0 | 1 ) (default: 1)
Whether SpamAssassin should automatically feed high-
scoring mails (or low-scoring mails, for non-spam)
into its learning systems. The only learning system
supported currently is a naive-Bayesian-style classi
fier. Note that certain tests are ignored when determining
whether a message should be trained upon:
- auto-whitelist (AWL)
- rules with tflags set to 'learn' (the Bayesian
rules)
- rules with tflags set to 'userconf' (user
white/black-listing rules, etc) Also note that auto-training occurs using scores from
either scoreset 0 or 1, depending on what scoreset is
used during message check. It is likely that the mes
sage check and auto-train scores will be different.----------
So when SA decided to autolearn, it saw only NO_REAL_NAME as a match, since the bayes subsystem is entirely discounted BAYES_90 isn't used.
The score entry is: score NO_REAL_NAME 0.993 0.820 1.137 1.149
So if you have no network checks, the email scored 0.993 for the purposes of autolearning. If you have network checks enabled, the score was 0.820 for the purpose of autolearning.
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