So, just exactly where is the documentation that defines the criteria for what gets auto learnt?
In short, the email is autolearned based on computing it's score as if bayes were disabled, and then comparing that score to a threshold you set.
The details are in man Mail::SpamAssassin::Conf:
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bayes_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 classifier.
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 message check and auto-train scores will be different.
bayes_auto_learn_threshold_nonspam n.nn (default: 0.1)
The score threshold below which a mail has to score, to be fed into SpamAssassin's learning systems automatically as a non-spam message.
bayes_auto_learn_threshold_spam n.nn (default: 12.0)
The score threshold above which a mail has to score, to be fed into SpamAssassin's learning systems automatically as a spam message.
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