Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (The Morgan Kaufmann Series in Data Management Systems)
Language: English
Published by Morgan Kaufmann 13/07/2005, 2005
Series: Book 16 of 22 - The Morgan Kaufmann Series in Data Management Systems
- Softcover
- Used
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- Title
- Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (The Morgan Kaufmann Series in Data Management Systems)
- Author
- Ian H. Witten, Eibe Frank
- Publisher
- Morgan Kaufmann 13/07/2005
- Publication year
- 2005
- Condition
- Very Good
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 0120884070
- ISBN 13
- 9780120884070
- Edition
- 2nd Edition
- Series
- Book 16 of 22: The Morgan Kaufmann Series in Data Management Systems
Data Mining, Second Edition, describes data mining techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references.
The highlights of this new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information on neural networks; a new section on Bayesian networks; and much more.
This text is designed for information systems practitioners, programmers, consultants, developers, information technology managers, specification writers as well as professors and students of graduate-level data mining and machine learning courses.
- Algorithmic methods at the heart of successful data mining―including tried and true techniques as well as leading edge methods
- Performance improvement techniques that work by transforming the input or output
"Synopsis" may belong to another edition of this title.
About the Author
Eibe Frank lives in New Zealand with his Samoan spouse and two lovely boys, but originally hails from Germany, where he received his first degree in computer science from the University of Karlsruhe. He moved to New Zealand to pursue his Ph.D. in machine learning under the supervision of Ian H. Witten and joined the Department of Computer Science at the University of Waikato as a lecturer on completion of his studies. He is now a professor at the same institution. As an early adopter of the Java programming language, he laid the groundwork for the Weka software described in this book. He has contributed a number of publications on machine learning and data mining to the literature and has refereed for many conferences and journals in these areas.
"About the title" may belong to another edition of this title.
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