Stochastic Modelling and Applied Probability

By: Luc Devroye, LÃ¡szlÃ³ GyÃ¶rfi, Gabor Lugosi

Write A Review

Hardcover | 1 March 1997

At a Glance

Hardcover
660 Pages

Dimensions(cm)
23.39 x 15.6 x 3.51

Hardcover

$219.00

or 4 interest-free payments of $54.75 with

Ships in 5 to 7 business days

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, tree 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.

Shipping

	Standard Shipping	Express Shipping
Metro postcodes:	$9.99	$14.95
Regional postcodes:	$9.99	$14.95
Rural postcodes:	$9.99	$14.95

How to return your order

At Booktopia, we offer hassle-free returns in accordance with our returns policy. If you wish to return an item, please get in touch with Booktopia Customer Care.

Additional postage charges may be applicable.

Defective items

If there is a problem with any of the items received for your order then the Booktopia Customer Care team is ready to assist you.

For more info please visit our Help Centre.

You Can Find This Book In

Non-Fiction Psychology Cognition & Cognitive Psychology Mathematics Probability & Statistics Computing & I.T.Computer Science Artificial Intelligence Pattern Recognition Applied Mathematics Computer Vision

Other Editions and Formats

Paperback

Published: 22nd November 2013

View Product

Preface
Introduction	p. 1
The Bayes Error	p. 9
Inequalities and Alternate Distance Measures	p. 21
Linear Discrimination	p. 39
Nearest Neighbor Rules	p. 61
Consistency	p. 91
Slow Rates of Convergence	p. 111
Error Estimation	p. 121
The Regular Histogram Rule	p. 133
Kernel Rules	p. 147
Consistency of the k-Nearest Neighbor Rule	p. 169
Vapnik-Chervonenkis Theory	p. 187
Combinatorial Aspects of Vapnik-Chervonenkis Theory	p. 215
Lower Bounds for Empirical Classifier Selection	p. 233
The Maximum Likelihood Principle	p. 249
Parametric Classification	p. 263
Generalized Linear Discrimination	p. 279
Complexity Regularization	p. 289
Condensed and Edited Nearest Neighbor Rules	p. 303
Tree Classifiers	p. 315
Data-Dependent Partitioning	p. 363
Splitting the Data	p. 387
The Resubstitution Estimate	p. 397
Deleted Estimates of the Error Probability	p. 407
Automatic Kernel Rules	p. 423
Automatic Nearest Neighbor Rules	p. 451
Hypercubes and Discrete Spaces	p. 461
Epsilon Entropy and Totally Bounded Sets	p. 479
Uniform Laws of Large Numbers	p. 489
Neural Networks	p. 507
Other Error Estimates	p. 549
Feature Extraction	p. 561
Appendix	p. 575
Notation	p. 591
References	p. 593
Author Index	p. 619
Subject Index	p. 627
Table of Contents provided by Blackwell. All Rights Reserved.

Stochastic Modelling and Applied Probability

At a Glance

Hardcover

Shipping

How to return your order

Defective items

You Can Find This Book In

Other Editions and Formats

Paperback

More in Pattern Recognition

Exploring GeoAI

Tools and Workflows

Making Sense of Modern Science

A Tour for the Curious

Markov Decision Processes and Reinforcement Learning

Complexity in Computer Science

Beyond Slop

Professional AI image creation

Modern Machine Learning and Pattern Recognition

AI Projects with Raspberry Pi

High-performance artificial intelligence for robotics, security, home automation, and vision

Mathematics for Machine Learning

Generative AI on AWS

Building Context-Aware Multimodal Reasoning Applications

Becoming an AI Researcher

Practical Advice for Graduate Students

Deep Learning for Finance

Creating Machine & Deep Learning Models for Trading in Python

Llms and Generative AI for Healthcare

The Next Frontier

Reinforcement Learning for Finance

A Python-Based Introduction

Individual-based Methods in Forest Ecology and Management

Introduction to Deep Learning

Neural Networks, Large Language Models and Agentic AI

Document Analysis Systems II

Series in Machine Perception and Artificial Intelligence

Ram-Based Neural Networks

Progress in Neural Processing, 9

Shape, Structure and Pattern Recognition

VLSI and Parallel Computing for Pattern Recognition and Artificial Intelligence

Series in Machine Perception and Artificial Intelligence

Intelligent Image Database Systems

Series on Software Engineering and Knowledge Engineering

Theory and Applications of Image Analysis II : Selected Papers from the 9th Scandinavian Conference on Image Analysis

Selected Papers from the 9th Scandinavian Conference on Image Analysis

Advances in Structural and Syntactic Pattern Recognition : Proceedings of the International Workshop on Structural and Syntactic Pattern Recognition, Bern, Switzerland, August 26-28, 1992

SERIES IN MACHINE PERCEPTION & ARTIFICIAL INTELL

Neural Networks for Pattern Recognition and Their Applications

State of the Art in Digital Mammographic Image Amalysis

Series in Machine Perception and Artificial Intelligence

This product is categorised by