Random graphs for statistical pattern recognition

David Marchette - Collection Wiley Series in Probability and Statistics

246 pages, parution le 30/03/2004

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Résumé

A timely convergence of two widely used disciplines Random Graphs for Statistical Pattern Recognition is the first book to address the topic of random graphs as it applies to statistical pattern recognition. Both topics are of vital interest to researchers in various mathematical and statistical fields and have never before been treated together in one book. The use of data random graphs in pattern recognition in clustering and classification is discussed, and the applications for both disciplines are enhanced with new tools for the statistical pattern recognition community. New and interesting applications for random graph users are also introduced.

This important addition to statistical literature features:

Information that previously has been available only through scattered journal articles
Practical tools and techniques for a wide range of real-world applications
New perspectives on the relationship between pattern recognition and computational geometry
Numerous experimental problems to encourage practical applications

With its comprehensive coverage of two timely fields, enhanced with many references and real-world examples, Random Graphs for Statistical Pattern Recognition is a valuable resource for industry professionals and students alike.

Sommaire

Preliminaries.
Computational Geometry.
Neighborhood Graphs.
Class Cover Catch Digraphs.
Cluster Catch Digraphs.
Computational Methods.

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	David Marchette
Collection	Wiley Series in Probability and Statistics
Parution	30/03/2004
Nb. de pages	246
Format	16 x 24
Couverture	Relié
Poids	569g
Intérieur	Noir et Blanc
EAN13	9780471221760
ISBN13	978-0-471-22176-0