Data Mining

Practical Machine Learning Tools and Techniques, Second Edition

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Database Management, General Computing
Cover of the book Data Mining by Ian H. Witten, Eibe Frank, Elsevier Science
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Author: Ian H. Witten, Eibe Frank ISBN: 9780080477022
Publisher: Elsevier Science Publication: July 13, 2005
Imprint: Morgan Kaufmann Language: English
Author: Ian H. Witten, Eibe Frank
ISBN: 9780080477022
Publisher: Elsevier Science
Publication: July 13, 2005
Imprint: Morgan Kaufmann
Language: English

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
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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