A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) (repost)
Luc Devroye, Laszlo Györfi, "A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability)"
English | 1996-04-04 | ISBN: 0387946187 | 654 pages | PDF | 10.7 mb
English | 1996-04-04 | ISBN: 0387946187 | 654 pages | PDF | 10.7 mb
Pattern recognition presents one of the most significant challenges for scientists and engineers and many different approaches have been proposed and developed. The aim of this book is to provide a self-contained and coherent account of probabilistic techniques which have been applied to the subject.
Amongst the topics covered are: distance measures, kernel rules, nearest neighbor rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further help a reader's understanding. Research workers and graduate students will benefit from this wide-ranging and up-to-date account of this fast-moving field.