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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 p. : ill. ; 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. |
| More information: | Publisher description | Table of contents only |
Abstract:
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, parametric classification, error estimation, tree classifiers, and neural networks.
Wherever possible, distribution-free properties and inequalities are derived. A substantial portion of the results or the analysis is new. Over 430 problems and exercises complement the material.
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