DATA MINING Practical Machine Learning Tools and Techniques, 3rd Ed (2011) pdf RUPOM

DATA MINING
Practical Machine Learning Tools and Techniques, 3rd Ed (2011)

TRUE PDF WITH BOOKMARKS & INDEX



Authors:
Ian H. Witten
Eibe Frank
Mark A. Hall
Imprint: Elsevier
Publisher: Morgan Kaufmann
Language : English
Pages: 665
Reader Required: Adobe Reader, Foxit, Nitro etc.
Published : January 20, 2011
ISBN: 978-0123748560


Contents:

Part I. Introduction to Data Mining
Chapter 01. What’s It All About?
Chapter 02. Input: Concepts, Instances, Attributes
Chapter 03. Output: Knowledge Representation
Chapter 04. Algorithms: The Basic Methods
Chapter 05. Credibility: Evaluating What’s Been Learned

Part II. Advanced Data Mining
Chapter 6. Implementations: Real Machine Learning Schemes
Chapter 7. Data Transformations
Chapter 8. Ensemble Learning
Chapter 9. Moving On: Applications and Beyond

Part III. The Weka Data Mining Workbench
Chapter 10. Introduction to Weka
Chapter 11. The Explorer
Chapter 12. The Knowledge Flow Interface
Chapter 13. The Experimenter
Chapter 14. The Command-Line Interface
Chapter 15. Embedded Machine Learning
Chapter 16. Writing New Learning Schemes
Chapter 17. Tutorial Exercises for the Weka Explorer