01-03-2019
Quote:
Hi Ravinder,
You are really doing a great service to the community here.
- Your badge system concept was a great idea and will prove to add more value to the community as it evolves over the years.
- Your work writing logic for badges while you learn PHP is absolutely the way to learn technology. It is always best, in my view, to learn by actually doing projects; not just watching YT tutorials and paying for online classes and certifications.
- Keep up the good work.
Thanks a TON Neo for encouragement here, even after 13 hours long day trying hard to learn at least 1 new thing daily.Will post soon docker's learning may be on coming weekend.
Thanks,
R. Singh
These 2 Users Gave Thanks to RavinderSingh13 For This Post:
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Today, I am very pleased to announce that the Moderator of the Year Award, 2019 has two very deserving winners.
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LEARN ABOUT SUSE
mail::spamassassin::plugin::autolearnthreshold
Mail::SpamAssassin::Plugin::AutoLearnThreshold(3) User Contributed Perl Documentation Mail::SpamAssassin::Plugin::AutoLearnThreshold(3)
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:
o rules with tflags set to 'learn' (the Bayesian rules)
o rules with tflags set to 'userconf' (user configuration)
o 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.
perl v5.12.1 2010-03-16 Mail::SpamAssassin::Plugin::AutoLearnThreshold(3)