- Advanced Splunk
- Table of Contents
- Advanced Splunk
- Credits
- About the Author
- Acknowledgements
- About the Reviewer
- www.PacktPub.com
- Preface
- 1. What's New in Splunk 6.3?
- 2. Developing an Application on Splunk
- 3. On-boarding Data in Splunk
- 4. Data Analytics
- 5. Advanced Data Analytics
- 6. Visualization
- 7. Advanced Visualization
- 8. Dashboard Customization
- 9. Advanced Dashboard Customization
- 10. Tweaking Splunk
- 11. Enterprise Integration with Splunk
- 12. What Next? Splunk 6.4
- Index
Splunk 6.4 has enhanced the Machine Learning Toolkit and Showcase app, which we already studied with an example in Chapter 5, Advanced Data Analytics. Splunk 6.4 comes with six new machine learning algorithms along with support to hundreds of algorithms of Python's data science library. Apart from this enhancement, the machine learning app has added the Guided ML feature that guides users step by step to build, test, and deploy machine learning models.
Splunk 6.4 has enhanced the predict command with features like these:
- A new algorithm for bivariate time series has been introduced, taking covariance between the individual time series into account for better and efficient prediction
- The
predictcommand can be used to predict results for multiple time series at the same time and can also fill in missing data in the given time series
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