1Mail::SpamAssassin::PluUgsienr::CAounMttaoriLileb:au:rtSnepTdahmrPAeessrshlaoslDsdoi(cn3u:)m:ePnltuagtiino:n:AutoLearnThreshold(3)
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6 Mail::SpamAssassin::Plugin::AutoLearnThreshold - threshold-based dis‐
7 criminator 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)
22 * rules with tflags set to 'userconf' (user configuration)
23 * rules with tflags set to 'noautolearn'
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25 Also note that auto-learning occurs using scores from either scoreset 0
26 or 1, depending on what scoreset is used during message check. It is
27 likely that the message check and auto-learn scores will be different.
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30 The following configuration settings are used to control auto-learning:
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32 bayes_auto_learn_threshold_nonspam n.nn (default: 0.1)
33 The score threshold below which a mail has to score, to be fed into
34 SpamAssassin's learning systems automatically as a non-spam mes‐
35 sage.
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37 bayes_auto_learn_threshold_spam n.nn (default: 12.0)
38 The score threshold above which a mail has to score, to be fed into
39 SpamAssassin's learning systems automatically as a spam message.
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41 Note: SpamAssassin requires at least 3 points from the header, and
42 3 points from the body to auto-learn as spam. Therefore, the mini‐
43 mum working value for this option is 6.
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47perl v5.8.8 Mail:2:0S0p8a-m0A1s-s0a5ssin::Plugin::AutoLearnThreshold(3)