Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)

Simovici, Dan A., Djeraba, Chabane

ISBN 10: 1848002009 / ISBN 13: 9781848002005

Edité par Springer, 2008

A propos de cet article

Very Good.

N° de réf. du vendeur D8S0-3-M-1848002009-4

Détails bibliographiques

• Titre: Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)
• Éditeur: Springer
• Date de parution: 2008
• Langue: anglais
• ISBN à 10 chiffres: 1848002009
• ISBN à 13 chiffres: 9781848002005
• Reliure: Hardcover
• État de l'article: Very Good
• Type de livre: book

A propos de ce titre

Synopsis

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.