Stochastic Modelling and Applied Probability

Devroye, Luc; Györfi, Laszlo; Lugosi, Gabor

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.

Details

Published by: Springer

Publication Date: 2013-11-22

Format: Paperback

ISBN-13: 9781461268772

DOI: 10.1007/978-1-4612-0711-5

Dimensions: 235cm x155cm

Pages: 638