You're reading from Machine Learning with the Elastic Stack Gain valuable insights from your data with Elastic Stack's machine learning features

Product type Paperback

Published in May 2021

Publisher Packt

ISBN-13 9781801070034

Length 450 pages

Edition 2nd Edition

Languages

Python

Tools

Elasticsearch

Concepts

Machine Learning

Authors (3):

Camilla Montonen

Rich Collier

Bahaaldine Azarmi

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Table of Contents (19) Chapters

Preface

1. Section 1 – Getting Started with Machine Learning with Elastic Stack

2. Chapter 1: Machine Learning for IT FREE CHAPTER

3. Chapter 2: Enabling and Operationalization

4. Section 2 – Time Series Analysis – Anomaly Detection and Forecasting

5. Chapter 3: Anomaly Detection

6. Chapter 4: Forecasting

7. Chapter 5: Interpreting Results

8. Chapter 6: Alerting on ML Analysis

9. Chapter 7: AIOps and Root Cause Analysis

10. Chapter 8: Anomaly Detection in Other Elastic Stack Apps

11. Section 3 – Data Frame Analysis

12. Chapter 9: Introducing Data Frame Analytics

13. Chapter 10: Outlier Detection

14. Chapter 11: Classification Analysis

15. Chapter 12: Regression

16. Chapter 13: Inference

17. Other Books You May Enjoy

Appendix: Anomaly Detection Tips

Understanding the advanced detector functions

In addition to the detector functions mentioned so far, there are also a few other, more advanced functions that allow some very unique capabilities. Some of these functions are only available if the ML job is configured via the advanced job wizard or via the API.

rare

In the context of a stream of temporal information (such as a log file), the notion of something being statistically rare (occurring at a low frequency) is paradoxically both intuitive and hard to understand. If I were asked, for example, to trawl through a log file and find a rare message, I might be tempted to label the first novel message that I saw as a rare one. But what if practically every message was novel? Are they all rare? Or is nothing rare?

In order to define rarity to be useful in the context of a stream of events in time, we need to agree that the declaration of something as being rare must take into account the context in which it exists. If there...