1Mail::SpamAssassin::PluUgsienr::CAounMttaoriLileb:au:rtSnepTdahmrPAeessrshlaoslDsdoi(cn3u:)m:ePnltuagtiino:n:AutoLearnThreshold(3)
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6 Mail::SpamAssassin::Plugin::AutoLearnThreshold - threshold-based
7 discriminator for Bayes auto-learning
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10 loadplugin Mail::SpamAssassin::Plugin::AutoLearnThreshold
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13 This plugin implements the threshold-based auto-learning discriminator
14 for SpamAssassin's Bayes subsystem. Auto-learning is a mechanism
15 whereby high-scoring mails (or low-scoring mails, for non-spam) are fed
16 into its learning systems without user intervention, during scanning.
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18 Note that certain tests are ignored when determining whether a message
19 should be trained upon:
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21 · rules with tflags set to 'learn' (the Bayesian rules)
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23 · rules with tflags set to 'userconf' (user configuration)
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25 · rules with tflags set to 'noautolearn'
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27 Also note that auto-learning occurs using scores from either scoreset 0
28 or 1, depending on what scoreset is used during message check. It is
29 likely that the message check and auto-learn scores will be different.
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32 The following configuration settings are used to control auto-learning:
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34 bayes_auto_learn_threshold_nonspam n.nn (default: 0.1)
35 The score threshold below which a mail has to score, to be fed into
36 SpamAssassin's learning systems automatically as a non-spam
37 message.
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39 bayes_auto_learn_threshold_spam n.nn (default: 12.0)
40 The score threshold above which a mail has to score, to be fed into
41 SpamAssassin's learning systems automatically as a spam message.
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43 Note: SpamAssassin requires at least 3 points from the header, and
44 3 points from the body to auto-learn as spam. Therefore, the
45 minimum working value for this option is 6.
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49perl v5.10.1 Mail:2:0S1p0a-m0A3s-s1a6ssin::Plugin::AutoLearnThreshold(3)