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Machine Learning with the Elastic Stack - Second Edition

You're reading from  Machine Learning with the Elastic Stack - Second Edition

Product type Book
Published in May 2021
Publisher Packt
ISBN-13 9781801070034
Pages 450 pages
Edition 2nd Edition
Languages
Authors (3):
Rich Collier Rich Collier
Profile icon Rich Collier
Camilla Montonen Camilla Montonen
Profile icon Camilla Montonen
Bahaaldine Azarmi Bahaaldine Azarmi
Profile icon Bahaaldine Azarmi
View More author details

Table of Contents (19) Chapters

Preface 1. Section 1 – Getting Started with Machine Learning with Elastic Stack
2. Chapter 1: Machine Learning for IT 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

Looking at forecast results

Now that we have run a forecast, we can look in more depth at the results that are generated by the forecasting process. We can view the results of a previously created forecast at any time in the UI via one of two methods. The first way is to click the Forecast button in Single Metric Viewer to reveal a list of previous forecasts, like so:

Figure 4.20 – Viewing previously created forecasts from Single Metric Viewer

Alternatively, you can view them in the Job Management page under the Forecasts tab for that job, as illustrated in the following screenshot:

Figure 4.21 – Viewing previously created forecasts from the Job Management page

Note

Forecast results built in Kibana have a default lifespan of 14 days. After that, the forecast results are deleted permanently. If a different expiration duration is desired, then the forecast will have to be invoked via the _forecast API endpoint, which...

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