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portada Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics
Type
Physical Book
Author
Publisher
Language
English
Pages
831
Format
Paperback
Dimensions
23.4 x 15.6 x 4.2 cm
Weight
1.16 kg.
ISBN13
9781447171348
Edition No.
0002
Categories

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

Dan A. Simovici (Author) · Chabane Djeraba (Author) · Springer · Paperback

Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics - Simovici, Dan A. ; Djeraba, Chabane

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

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.

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