Mathematical Tools for Data Mining
Set Theory, Partial Orders, Combinatorics
2nd Edition
Published on 27. March 2014
XI, 831 pages
978-1-4471-6407-4 (ISBN)
Description
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.
Reviews / Votes
From the book reviews:
"This textbook is appropriate for an advanced undergraduate or graduate mathematics elective class. All theorems are proved, notation is standard, and ample exercise sets are included at the end of every chapter. . Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics is more than just the data-mining reference book. It is highly readable textbook that successfully connects classic, theoretical mathematics to an enormously popular current application in modern society." (Susan D'Agostino, MAA Reviews, March, 2015)
"The goal of this book is to present the basic mathematical theory and principles used in data mining tools and techniques. . Graduate or advanced undergraduate students with prior coursework in mathematics will find this book a useful collection of the fundamental mathematical ideas . . The exposition of concepts is clear and readable. Comfort with mathematical notation is necessary, since the book makes significant use of such notation. Several exercises are included, with solutions being provided in outline." (R. M. Malyankar, Computing Reviews, September, 2014)More details
Series
Edition
2nd ed. 2014
Language
English
Place of publication
London
United Kingdom
Publishing group
Springer London
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XI, 831 p. 93 illus.
File size
9,06 MB
ISBN-13
978-1-4471-6407-4 (9781447164074)
DOI
10.1007/978-1-4471-6407-4
Schweitzer Classification
Other editions
Additional editions
Dan A. Simovici | Chabane Djeraba
Mathematical Tools for Data Mining
Set Theory, Partial Orders, Combinatorics
Book
04/2014
2nd Edition
Springer
€192.59
Shipment within 15-20 days
Previous edition
Dan A. Simovici | Chaabane Djeraba
Mathematical Tools for Data Mining
Set Theory, Partial Orders, Combinatorics
E-Book
08/2008
1st Edition
Springer
€149.79
Available for download
Content
Sets, Relations and Functions.- Partially Ordered Sets.- Combinatorics.- Topologies and Measures.- Linear Spaces.- Norms and Inner Products.- Spectral Properties of Matrices.- Metric Spaces Topologies and Measures.- Convex Sets and Convex Functions.- Graphs and Matrices.- Lattices and Boolean Algebras.- Applications to Databases and Data Mining.- Frequent Item Sets and Association Rules.- Special Metrics.- Dimensions of Metric Spaces.- Clustering.
