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Implementing Splunk 7, Third Edition

You're reading from   Implementing Splunk 7, Third Edition Effective operational intelligence to transform machine-generated data into valuable business insight

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788836289
Length 576 pages
Edition 3rd Edition
Languages
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Author (1):
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James D. Miller James D. Miller
Author Profile Icon James D. Miller
James D. Miller
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Table of Contents (15) Chapters Close

Preface 1. The Splunk Interface FREE CHAPTER 2. Understanding Search 3. Tables, Charts, and Fields 4. Data Models and Pivots 5. Simple XML Dashboards 6. Advanced Search Examples 7. Extending Search 8. Working with Apps 9. Building Advanced Dashboards 10. Summary Indexes and CSV Files 11. Configuring Splunk 12. Advanced Deployments 13. Extending Splunk 14. Machine Learning Toolkit

Assistants

The Splunk Machine Learning Toolkit provides (as of writing) six assistants as shown in the following screenshot:

 These assistants are provided to you as, sort of, wizards that provide step-by-step guidance to create a machine learning model with a particular purpose or objective.

The Splunk product describes these assistants as follows:

"Each assistant includes end-to-end examples with datasets, plus the ability to apply the visualizations and SPL commands to your own data..."

These six assisted models are based on six of (perhaps) the most common models a data scientist may build.

They include:

  • Predict Numeric Fields (linear regression): For example, predict median house values
  • Predict Categorical Fields (linear regression): For example, predict customer churn
  • Detect Numeric Outliers (distribution statistics): For example, detect outliers in...
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