A probabilistic theory of pattern recognition (Book, 1996) [WorldCat.org]
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A probabilistic theory of pattern recognition

Author: Luc Devroye; László Györfi; Gábor Lugosi
Publisher: New York : Springer, ©1996.
Series: Applications of mathematics, 31.
Edition/Format:   Print book : EnglishView all editions and formats
Pattern recognition presents one of the most significant challenges for scientists and engineers, and many different approaches have been proposed. The aim of this book is to provide a self-contained account of probabilistic analysis of these approaches. The book includes a discussion of distance measures, nonparametric methods based on kernels or nearest neighbors, Vapnik-Chervonenkis theory, epsilon entropy,

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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Luc Devroye; László Györfi; Gábor Lugosi
ISBN: 0387946187 9780387946184
OCLC Number: 33276839
Description: xv, 636 pages : illustrations ; 24 cm
Contents: Introduction --
The Bayes Error --
Inequalities and alternate distance measures --
Linear discrimination --
Nearest neighbor rules --
Consistency --
Slow rates of convergence --
Error estimation --
The regular histogram rule --
Kernel rules --
Consistency of the k-nearest neighbor rule --
Vapnik-Chervonenkis theory --
Combinatorial aspects of Vapnik-Chervonenkis theory --
Lower bounds for empirical classifier selection --
The maximum likelihood principle --
Parametric classification --
Generalized linear discrimination --
Complexity regularization --
Condensed and edited nearest neighbor rules --
Tree classifiers --
Data-dependent partitioning --
Splitting the data --
The resubstitution estimate --
Deleted estimates of the error probability --
Automatic kernel rules --
Automatic nearest neighbor rules --
Hypercubes and discrete spaces --
Epsilon entropy and totally bounded sets --
Uniform laws of large numbers --
Neural networks --
Other error estimates --
Feature extraction.
Series Title: Applications of mathematics, 31.
Responsibility: Luc Devroye, László Györfi, Gábor Lugosi.
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A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and  Read more...


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