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Data Mining: Know It All
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  • Data Mining: Know It All
ID: 171653
Soumen Chakrabarti, Earl Cox, Eibe Frank, Ralf Güting, Jiawei Han, Xia Jiang, Micheline Kamber, Sam Lightstone, Thomas Nadeau, Richard E. Neapolitan, Dorian Pyle, Mamdouh Refaat, Markus Schneider, Toby Teorey, Ian Witten
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This book brings all the elements together in a single volume, saving the book and expense of making multiple purchases. It consolidates both introductory and advanced topics, and covers the gamut of data mining and machine learning tactics? from data integration and pre-processing, to fundamental algorithms, to optimization techniques and web mining methodology.

The proposed book expertly combines the finest data mining from Morgan Kaufmann portfolio. Individual chapters are derived from MK books authored by the best and brightest in the field. These chapters are combined into a comprehensive system.

This book is a quick and effective way to get the most out of your mind, a one-stop shopping experience.


  • Chapters contributing to multiple viewpoints.

  • Presents multiple methods of analysis and algorithmic problem-solving techniques.

  • Coverage of both theories and expositions.


Chapter 1: Data Mining Overview
Chapter 2: Data Acquisition and Integration
Chapter 3: Data Pre-processing
Chapter 4: Physical Design for Decision Support, Warehousing, and OLAP
Chapter 5: Algorithms - The Basic Methods
Chapter 6: Further Techniques in Decision Analysis
Chapter 7: Fundamental Concepts of Genetic Algorithms
Chapter 8: Spatio-Temporal Data Structures and Algorithms for Moving Objects Types
Chapter 9: Improving the Mined Model
Chapter 10: Web Mining - Social Network Analysis
171653

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