A Probabilistic Theory of Pattern Recognition

A Probabilistic Theory of Pattern Recognition
Author :
Publisher : Springer Science & Business Media
Total Pages : 631
Release :
ISBN-10 : 9781461207115
ISBN-13 : 1461207118
Rating : 4/5 (118 Downloads)

Book Synopsis A Probabilistic Theory of Pattern Recognition by : Luc Devroye

Download or read book A Probabilistic Theory of Pattern Recognition written by Luc Devroye and published by Springer Science & Business Media. This book was released on 2013-11-27 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: A self-contained and coherent account of probabilistic techniques, covering: 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.


A Probabilistic Theory of Pattern Recognition Related Books

A Probabilistic Theory of Pattern Recognition
Language: en
Pages: 631
Authors: Luc Devroye
Categories: Mathematics
Type: BOOK - Published: 2013-11-27 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theor
Pattern Recognition and Machine Learning
Language: en
Pages: 0
Authors: Christopher M. Bishop
Categories: Computers
Type: BOOK - Published: 2016-08-23 - Publisher: Springer

DOWNLOAD EBOOK

This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approxi
Machine Learning
Language: en
Pages: 1102
Authors: Kevin P. Murphy
Categories: Computers
Type: BOOK - Published: 2012-08-24 - Publisher: MIT Press

DOWNLOAD EBOOK

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. Today's Web-enabled deluge of electronic d
Principles of Nonparametric Learning
Language: en
Pages: 344
Authors: Laszlo Györfi
Categories: Technology & Engineering
Type: BOOK - Published: 2014-05-04 - Publisher: Springer

DOWNLOAD EBOOK

This volume provides a systematic in-depth analysis of nonparametric learning. It covers the theoretical limits and the asymptotical optimal algorithms and esti
Probabilistic Machine Learning
Language: en
Pages: 858
Authors: Kevin P. Murphy
Categories: Computers
Type: BOOK - Published: 2022-03-01 - Publisher: MIT Press

DOWNLOAD EBOOK

A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This boo