A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) Softcover reprint of edition by Devroye, Luc, Györfi, László, Lugosi, Gabor (2013) Paperback

by Luc Devroye

A self-contained and coherent account of probabilistic techniques, distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.

Genres: Textbooks, Mathematics

Paperback

First published February 20, 1996

Reviews

[Richard Zhu · Rating 4 out of 5]

> Pattern recognition is thus easier than regression function estimation.

Worth reading for this section alone