1Mail::SpamAssassin::PluUgsienr::CAounMttaoriLileb:au:rtSnepTdahmrPAeessrshlaoslDsdoi(cn3u:)m:ePnltuagtiino:n:AutoLearnThreshold(3)
2
3
4

NAME

6       Mail::SpamAssassin::Plugin::AutoLearnThreshold - threshold-based
7       discriminator for Bayes auto-learning
8

SYNOPSIS

10         loadplugin     Mail::SpamAssassin::Plugin::AutoLearnThreshold
11

DESCRIPTION

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.
17
18       Note that certain tests are ignored when determining whether a message
19       should be trained upon:
20
21       •   rules with tflags set to 'learn' (the Bayesian rules)
22
23       •   rules with tflags set to 'userconf' (user configuration)
24
25       •   rules with tflags set to 'noautolearn'
26
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.
30

USER OPTIONS

32       The following configuration settings are used to control auto-learning:
33
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.
38
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.
42
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.
46
47           If test option "autolearn_header" or "autolearn_body" is set,
48           points from that rule are forced to count as coming from header or
49           body accordingly.  This can be useful for adjusting some meta
50           rules.
51
52           If the test option "autolearn_force" is set, the minimum value will
53           remain at 6 points but there is no requirement that the points come
54           from body and header rules.  This option is useful for autolearning
55           with rules that are considered to be extremely safe indicators of
56           the spaminess of a message.
57
58       bayes_auto_learn_on_error (0 | 1)        (default: 0)
59           With "bayes_auto_learn_on_error" off, autolearning will be
60           performed even if bayes classifier already agrees with the new
61           classification (i.e.  yielded BAYES_00 for what we are now trying
62           to teach it as ham, or yielded BAYES_99 for spam). This is a
63           traditional setting, the default was chosen to retain backward
64           compatibility.
65
66           With "bayes_auto_learn_on_error" turned on, autolearning will be
67           performed only when a bayes classifier had a different opinion from
68           what the autolearner is now trying to teach it (i.e. it made an
69           error in judgement). This strategy may or may not produce better
70           future classifications, but usually works very well, while also
71           preventing unnecessary overlearning and slows down database growth.
72
73
74
75perl v5.38.0                 Mail:2:0S2p3a-m0A7s-s2a2ssin::Plugin::AutoLearnThreshold(3)