Statistical Pattern Recognition, 2nd Edition

By Andrew R. Webb and Keith D. Copsey

Book Overview

Statistical Pattern Recognition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields, including the areas of engineering, statistics, computer science and the social sciences. The book describes techniques for analysing data comprising measurements made on individuals or objects. The techniques are used to make a prediction such as disease of a patient, the type of object illuminated by a radar, economic forecast. Emphasis is placed on techniques for classification, a term used for predicting the class or group an object belongs to (based on a set of exemplars) and for methods that seek to discover natural groupings in a data set. Each section concludes with a description of the wide range of practical applications that have been addressed and the further developments of theoretical techniques and includes a variety of exercises, from 'open-book' questions to more lengthy projects. New material is presented, including the analysis of complex networks and basic techniques for analysing the properties of datasets and also introduces readers to the use of variational methods for Bayesian density estimation and looks at new applications in biometrics and security.

• Format: Paperback
• Language: English
• ISBN: 0470682280
• ISBN13: 9780470682289
• Release Date: November 2011
• Publisher: Wiley
• Length: 672 Pages
• Weight: 2.43 lbs.
• Dimensions: 1.4" x 6.6" x 9.5"

Customer Reviews

The most comprehensive book about machine learning

The book written by Andrew Webb is certainly the most comprehensive book related to machine learning. I have not been able to find any machine learning topic which is not treated in this book. According to me, this book is more for a scientific audience for the simplest reason that the presentation gives more importance to equations than to application examples. It does not explain how to program machine learning algorithm...

This book is good guidance.

I recently started study about Pattern Recognition. This book is so well organized. - Introduction to statistical pattern recognition- Basic approaches to supervised classification via Bayes' rule and estimation of the class-conditional densities.- Discriminant function approach to supervised classification.- Techniques of exploratory data analysis.- Additional topics on pattern recognition including performance assessment.Especially,...