A Probabilistic Theory of Pattern Recognition

Luc Devroye, Laszlo Györfi, Gabor Lugosi (Autoren)

Buch | Softcover

638 Seiten

2013 | Softcover reprint of the original 1st ed. 1996
Springer-Verlag New York Inc.
978-1-4612-6877-2 (ISBN)

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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, free 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.

Preface * 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 * Appendix * Notation * References * Index

Reihe/Serie	Stochastic Modelling and Applied Probability ; 31
Zusatzinfo	XV, 638 p.
Verlagsort	New York, NY
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Themenwelt	Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
ISBN-10	1-4612-6877-X / 146126877X
ISBN-13	978-1-4612-6877-2 / 9781461268772
Zustand	Neuware