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Data Mining Methods for Knowledge Discovery

Data Mining Methods for Knowledge Discovery

Data Mining Methods for Knowledge Discovery
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Data Mining Methods for Knowledge Discovery Hardback - 1998

by Pedrycz, Witold, Swiniarski, Roman W., Cios, Krzysztof J

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Springer. Used - Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
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Details

  • Title Data Mining Methods for Knowledge Discovery
  • Author Pedrycz, Witold, Swiniarski, Roman W., Cios, Krzysztof J
  • Binding Hardback
  • Edition 1st
  • Condition Used - Good
  • Pages 495
  • Volumes 1
  • Language ENG
  • Publisher Springer
  • Publication date 1998-08-31
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • Bookseller's Inventory # GRP82677266
  • ISBN 9780792382522 / 0792382528
  • Weight 1.85 lbs (0.84 kg)
  • Dimensions 9.02 x 7.04 x 1.13 in (22.91 x 17.88 x 2.87 cm)
  • Category Computers - General Information
  • Library of Congress subjects Database management, Data mining
  • Library of Congress Catalogue Number 98029384
  • Dewey Decimal Code 006.3
  • Quantity available 1

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Reader reviews for Data Mining Methods for Knowledge Discovery

From the publisher

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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