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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics
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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics Hardback - 2014

by Dan A. Simovici; Chabane Djeraba

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From the publisher

Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, graph theory. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc. The book is intended as a reference for researchers and graduate students. The current edition is a significant expansion of the first edition. We strived to make the book self-contained and only a general knowledge of mathematics is required. More than 700 exercises are included and they form an integral part of the material. Many exercises are in reality supplemental material and their solutions are included.

From the rear cover

Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, graph theory. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc. The book is intended as a reference for researchers and graduate students.

The current edition is a significant expansion of the first edition. We strived to make the book self-contained, and only a general knowledge of mathematics is required. More than 700 exercises are included and they form an integral part of the material. Many exercises are in reality supplemental material and their solutions are included.

Details

  • Title Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics
  • Author Dan A. Simovici; Chabane Djeraba
  • Binding Hardback
  • Pages 831
  • Volumes 1
  • Language ENG
  • Publisher Springer
  • Publication date 2014-04-09
  • Illustrated Yes
  • Features Illustrated
  • ISBN 9781447164067 / 1447164067
  • Weight 2.75 lbs (1.25 kg)
  • Dimensions 9.2 x 6.2 x 1.9 in (23.37 x 15.75 x 4.83 cm)
  • Themes
    • Aspects (Academic): Science/Technology Aspects
  • Category Computers - Data Base Management
  • Dewey Decimal Code 004.015
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Mathematical Tools for Data Mining : Set Theory, Partial Orders, Combinatorics

Mathematical Tools for Data Mining : Set Theory, Partial Orders, Combinatorics

by Dan A. Simovici

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Hardcover. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, g
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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)

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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics
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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics

by Simovici, Dan A. (Author)/ Djeraba, Chabane (Author)

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Mathematical Tools For Data Mining: Set Theory, Partial Orders, Combinatorics, 2Nd Edition
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Mathematical Tools For Data Mining: Set Theory, Partial Orders, Combinatorics, 2Nd Edition

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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced...
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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)

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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)

by Simovici, Dan A

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Mathematical Tools for Data Mining
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Mathematical Tools for Data Mining

by Chabane Djeraba Dan A. Simovici

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