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Data Mining Methods for Knowledge Discovery (The Kluwer International Series in Engineering and Computer Science)

Data Mining Methods for Knowledge Discovery (The Kluwer International Series in Engineering and Computer Science)

Data Mining Methods for Knowledge Discovery (The Kluwer International Series in
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Data Mining Methods for Knowledge Discovery (The Kluwer International Series in Engineering and Computer Science) Hardback - 1998

by Cios, KJ et al

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  • Hardback

Description

Kluwer Academic, 1998. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780792382522
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Details

  • Title Data Mining Methods for Knowledge Discovery (The Kluwer International Series in Engineering and Computer Science)
  • Author Cios, KJ et al
  • Binding Hardback
  • Edition 1st
  • Pages 495
  • Volumes 1
  • Language ENG
  • Publisher Kluwer Academic
  • Publication date 1998
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • Bookseller's Inventory # 9290225
  • 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

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Reader reviews for Data Mining Methods for Knowledge Discovery (The Kluwer International Series in Engineering and Computer Science)

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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