NAME

       Mail::SpamAssassin::Plugin::AutoLearnThreshold - threshold-based discriminator for Bayes
       auto-learning

SYNOPSIS

         loadplugin     Mail::SpamAssassin::Plugin::AutoLearnThreshold

DESCRIPTION

       This plugin implements the threshold-based auto-learning discriminator for SpamAssassin's
       Bayes subsystem.  Auto-learning is a mechanism whereby high-scoring mails (or low-scoring
       mails, for non-spam) are fed into its learning systems without user intervention, during
       scanning.

       Note that certain tests are ignored when determining whether a message should be trained
       upon:

       •   rules with tflags set to 'learn' (the Bayesian rules)

       •   rules with tflags set to 'userconf' (user configuration)

       •   rules with tflags set to 'noautolearn'

       Also note that auto-learning 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-
       learn scores will be different.

USER OPTIONS

       The following configuration settings are used to control auto-learning:

       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.

           Note: SpamAssassin requires at least 3 points from the header, and 3 points from the
           body to auto-learn as spam.  Therefore, the minimum working value for this option is
           6.

           If the test option autolearn_force is set, the minimum value will remain at 6 points
           but there is no requirement that the points come from body and header rules.  This
           option is useful for autolearning with rules that are considered to be extremely safe
           indicators of the spaminess of a message.

       bayes_auto_learn_on_error (0 | 1)        (default: 0)
           With "bayes_auto_learn_on_error" off, autolearning will be performed even if bayes
           classifier already agrees with the new classification (i.e.  yielded BAYES_00 for what
           we are now trying to teach it as ham, or yielded BAYES_99 for spam). This is a
           traditional setting, the default was chosen to retain backward compatibility.

           With "bayes_auto_learn_on_error" turned on, autolearning will be performed only when a
           bayes classifier had a different opinion from what the autolearner is now trying to
           teach it (i.e. it made an error in judgement). This strategy may or may not produce
           better future classifications, but usually works very well, while also preventing
           unnecessary overlearning and slows down database growth.

perl v5.22.1                                20Mail::SpamAssassin::Plugin::AutoLearnThreshold(3pm)