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.IX Title "Mail::SpamAssassin::Plugin::AutoLearnThreshold 3pm"
.TH Mail::SpamAssassin::Plugin::AutoLearnThreshold 3pm "2021-03-26" "perl v5.28.1" "User Contributed Perl Documentation"
.\" For nroff, turn off justification.  Always turn off hyphenation; it makes
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.SH "NAME"
Mail::SpamAssassin::Plugin::AutoLearnThreshold \- threshold\-based discriminator for Bayes auto\-learning
.SH "SYNOPSIS"
.IX Header "SYNOPSIS"
.Vb 1
\&  loadplugin     Mail::SpamAssassin::Plugin::AutoLearnThreshold
.Ve
.SH "DESCRIPTION"
.IX Header "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.
.PP
Note that certain tests are ignored when determining whether a message
should be trained upon:
.IP "\(bu" 4
rules with tflags set to 'learn' (the Bayesian rules)
.IP "\(bu" 4
rules with tflags set to 'userconf' (user configuration)
.IP "\(bu" 4
rules with tflags set to 'noautolearn'
.PP
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.
.SH "USER OPTIONS"
.IX Header "USER OPTIONS"
The following configuration settings are used to control auto-learning:
.IP "bayes_auto_learn_threshold_nonspam n.nn   (default: 0.1)" 4
.IX Item "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.
.IP "bayes_auto_learn_threshold_spam n.nn      (default: 12.0)" 4
.IX Item "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.
.Sp
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.
.Sp
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.
.IP "bayes_auto_learn_on_error (0 | 1)        (default: 0)" 4
.IX Item "bayes_auto_learn_on_error (0 | 1) (default: 0)"
With \f(CW\*(C`bayes_auto_learn_on_error\*(C'\fR off, autolearning will be performed
even if bayes classifier already agrees with the new classification (i.e.
yielded \s-1BAYES_00\s0 for what we are now trying to teach it as ham, or yielded
\&\s-1BAYES_99\s0 for spam). This is a traditional setting, the default was chosen
to retain backward compatibility.
.Sp
With \f(CW\*(C`bayes_auto_learn_on_error\*(C'\fR 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.