Mathematical Tools for Data Mining Set Theory, Partial Orders, C
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 th
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Dan A. Simovici Chabane Djeraba
Mathematical Tools for Data Mining Set Theory, Partial Orders, Combinatorics Second Edition
Mathematical Tools for Data Mining
Advanced Information and Knowledge Processing Series editors Professor Lakhmi Jain [email protected] Professor Xindong Wu [email protected]
For further volumes: http://www.springer.com/series/4738
Dan A. Simovici Chabane Djeraba •
Mathematical Tools for Data Mining Set Theory, Partial Orders, Combinatorics
Second Edition
123
Dan A. Simovici MS, MS, Ph.D. University of Massachusetts Boston USA
Chabane Djeraba BSc, MSc, Ph.D. University of Sciences and Technologies of Lille Villeneuve d’Ascq France
ISSN 1610-3947 ISBN 978-1-4471-6406-7 ISBN 978-1-4471-6407-4 DOI 10.1007/978-1-4471-6407-4 Springer London Heidelberg New York Dordrecht
(eBook)
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Preface
The data mining literature contains many excellent titles that address the needs of users with a variety of interests ranging from decision making to pattern investigation in biological data. However, these books do not deal with the mathematical tools that are currently needed by data mining researchers and doctora
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