Book descriptionThis book brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. It consolidates both introductory and advanced topics, thereby covering 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 material from the Morgan Kaufmann portfolio. Individual chapters are derived from a select group of MK books authored by the best and brightest in the field. These chapters are combined into one comprehensive volume in a way that allows it to be used as a reference work for those interested in new and developing aspects of data mining.
This book represents a quick and efficient way to unite valuable content from leading data mining experts, thereby creating a definitive, one-stop-shopping opportunity for customers to receive the information they would otherwise need to round up from separate sources.
- Chapters contributed by various recognized experts in the field let the reader remain up to date and fully informed from multiple viewpoints.
- Presents multiple methods of analysis and algorithmic problem-solving techniques, enhancing the reader’s technical expertise and ability to implement practical solutions.
- Coverage of both theory and practice brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases.
Table of contents
- Brief Table of Contents
- Table of Contents
- List of Figures
- List of Tables
- Copyright Page
- About This Book
- Contributing Authors
- Chapter 1. What's It All About?
- Chapter 2. Data Acquisition and Integration
- Chapter 3. Data Preprocessing
Chapter 4. Physical Design for Decision Support, Warehousing, and OLAP
- 4.1. What Is Online Analytical Processing?
- 4.2. Dimension Hierarchies
- 4.3. Star and Snowflake Schemas
- 4.4. Warehouses and Marts
- 4.5. Scaling Up the System
- 4.6. DSS, Warehousing, and OLAP Design Considerations
- 4.7. Usage Syntax and Examples for Major Database Servers
- 4.8. Summary
- 4.9. Literature Summary
- Chapter 5. Algorithms: The Basic Methods
- Chapter 6. Further Techniques in Decision Analysis
- Chapter 7. Fundamental Concepts of Genetic Algorithms
- Chapter 8. Data Structures and Algorithms for Moving Objects Types
- Chapter 9. Improving the Model
- Chapter 10. Social Network Analysis
- Title: Data Mining: Know It All
- Release date: October 2008
- Publisher(s): Morgan Kaufmann
- ISBN: 9780080877884
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