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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing) Hardback - 2014
by Simovici, Dan A
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Details
- Title Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)
- Author Simovici, Dan A
- Binding Hardback
- Condition New
- Pages 831
- Volumes 1
- Language ENG
- Publisher Springer
- Publication date 2014-04-09
- Illustrated Yes
- Features Illustrated
- Bookseller's Inventory # 21282128-n
- 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)
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Themes
- Aspects (Academic): Science/Technology Aspects
- Category Computers - Data Base Management
- Dewey Decimal Code 004.015
- Quantity available 5
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From the publisher
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.
