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

• Main Authors: Jain, Lakhmi C, Wu, Xindong
• Format: eBook Book
• Language: English
• Published: London Springer Verlag London Limited 2008; Springer London, Limited; Springer London; Springer
• Edition: 1. Aufl.
• Series: Advanced Information and Knowledge Processing
• Subjects: Computational Mathematics and Numerical Analysis; Computer Science; Data mining; Data Mining and Knowledge Discovery; Discrete Mathematics in Computer Science; Mathematics of Computing; Metric spaces; Partially ordered sets; Set theory; Computer Software
• ISBN: 1848002009; 9781848002005
• ISSN: 1610-3947; 2197-8441
• DOI: 10.1007/978-1-84800-201-2

This book integrates the mathematics of data mining with its applications, offering the reader a reference to the mathematical tools required for data mining. Dedicated to the study of set-theoretical foundations of data mining, this book is focused on set theory and several closely related areas: partially ordered sets and lattice theory, metric spaces and combinatorics. The book is structured into 4 parts and presents a comprehensive discussion of the subject. Features and topics include: - Study of functions and relations, - Applications are provided throughout, - Presents graphs and hypergraphs, - Covers partially ordered sets, lattices and Boolean algebras, - Finite partially ordered sets, - Focuses on metric spaces, - Includes combinatorics, - Discusses the theory of the Vapnik-Chervonenkis dimension of collections of sets. Intended as a reference for the working data miner and researchers, a good knowledge of calculus is required to make the best use of this book, which will prove a useful reference.