A Probabilistic Theory of Pattern Recognition (Paperback, Softcover reprint of the original 1st ed. 1996)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Stochastic Modelling and Applied Probability, 31
Release date:	November 2013
First published:	1996
Authors:	Luc Devroye • Laszlo Gyoerfi • Gabor Lugosi
Dimensions:	235 x 155 x 34mm (L x W x T)
Format:	Paperback
Pages:	638
Edition:	Softcover reprint of the original 1st ed. 1996
ISBN-13:	978-1-4612-6877-2
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > Applications of computing > Pattern recognition
LSN:	1-4612-6877-X
Barcode:	9781461268772

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!