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Machine Learning with the Elastic Stack

You're reading from   Machine Learning with the Elastic Stack Expert techniques to integrate machine learning with distributed search and analytics

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788477543
Length 304 pages
Edition 1st Edition
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Authors (2):
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Bahaaldine Azarmi Bahaaldine Azarmi
Author Profile Icon Bahaaldine Azarmi
Bahaaldine Azarmi
Rich Collier Rich Collier
Author Profile Icon Rich Collier
Rich Collier
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Toc

Table of Contents (12) Chapters Close

Preface Machine Learning for IT FREE CHAPTER Installing the Elastic Stack with Machine Learning Event Change Detection IT Operational Analytics and Root Cause Analysis Security Analytics with Elastic Machine Learning Alerting on ML Analysis Using Elastic ML Data in Kibana Dashboards Using Elastic ML with Kibana Canvas Forecasting ML Tips and Tricks Other Books You May Enjoy

Ignoring time periods

Often, people ask how they can get ML to ignore that a certain time period has occurred. Perhaps it was an expected maintenance window, or perhaps something was broken within the data ingest pipeline and data was lost for a few moments. There are a few ways that you can get ML to ignore time periods and, for distinction, we'll separate them into two groups:

  • A known, upcoming window of time
  • An unexpected window of time that is discovered after the fact

To illustrate things, we'll use a reference job and dataset that has an anomaly on the date of February 9th:

Ignoring an upcoming (known) window of time

Two methods can be used to ignore an upcoming window of time, as shown in the following...

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