Mathematical Tools for Data Mining : Set Theory, Partial Orders, Combinatorics
2nd ed. 2014
Book Details
Format
Hardback or Cased Book
Book Series
Advanced Information and Knowledge Processing
ISBN-10
1447164067
ISBN-13
9781447164067
Edition
2nd ed. 2014
Publisher
Springer London Ltd
Imprint
Springer London Ltd
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Apr 9th, 2014
Print length
831 Pages
Weight
1,394 grams
Dimensions
16.40 x 23.90 x 4.90 cms
Ksh 28,800.00
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Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. 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.
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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