Provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book elaborates on the fundamentals of each of the data mining methods. It discusses these methods in the setting of the overall process of knowledge discovery. It is intended for senior undergraduate and graduate students. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 495 pages, biography. BIC Classification: UN. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 241 x 164 x 34. Weight in Grams: 896. . 1998. Hardback. . . . . Books ship from the US and Ireland.

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Bibliographic Details

Title: Data Mining Methods for Knowledge Discovery
Publisher: Kluwer Academic Publishers
Publication Date: 1998
Language: English
ISBN 10: 0792382528
ISBN 13: 9780792382522
Binding: Hardcover
Condition: New

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Synopsis

Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets, genetic algorithms, machine learning, neural networks, and preprocessing techniques. The book then goes on to thoroughly discuss these methods in the setting of the overall process of knowledge discovery. Numerous illustrative examples and experimental findings are also included. Each chapter comes with an extensive bibliography.
Data Mining Methods for Knowledge Discovery is intended for senior undergraduate and graduate students, as well as a broad audience of professionals in computer and information sciences, medical informatics, and business information systems.

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