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The Lounge What is on Your Mind? Ravinder Singh Just Earned His Green Web Dev Ops Badge Post 303028270 by RavinderSingh13 on Thursday 3rd of January 2019 07:42:33 AM
Old 01-03-2019
Quote:
Originally Posted by Neo
Hi Ravinder,
You are really doing a great service to the community here.
  1. Your badge system concept was a great idea and will prove to add more value to the community as it evolves over the years.
  2. 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.
  3. 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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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)
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