To see accurate pricing, please choose your delivery country.
 
 
United States
£ GBP
All Shops

British Wildlife

8 issues per year 84 pages per issue Subscription only

British Wildlife is the leading natural history magazine in the UK, providing essential reading for both enthusiast and professional naturalists and wildlife conservationists. Published eight times a year, British Wildlife bridges the gap between popular writing and scientific literature through a combination of long-form articles, regular columns and reports, book reviews and letters.

Subscriptions from £33 per year

Conservation Land Management

4 issues per year 44 pages per issue Subscription only

Conservation Land Management (CLM) is a quarterly magazine that is widely regarded as essential reading for all who are involved in land management for nature conservation, across the British Isles. CLM includes long-form articles, events listings, publication reviews, new product information and updates, reports of conferences and letters.

Subscriptions from £26 per year
Academic & Professional Books  Reference  Data Analysis & Modelling  Data Analysis & Statistics

Statistical Pattern Recognition

Textbook
By: Andrew R Webb(Author), Keith D Copsey(Author)
642 pages, b/w illustrations
Statistical Pattern Recognition
Click to have a closer look
Select version
  • Statistical Pattern Recognition ISBN: 9780470682289 Edition: 3 Paperback Oct 2011 Not in stock: Usually dispatched within 6 days
    £53.95
    #216270
  • Statistical Pattern Recognition ISBN: 9780470682272 Edition: 3 Hardback Oct 2011 Not in stock: Usually dispatched within 6 days
    £107.95
    #196910
Selected version: £53.95
About this book Contents Customer reviews Related titles

About this book

Statistical Pattern Recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques.

This third edition 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. Statistical Pattern Recognition has been updated to cover new methods and applications, and includes a wide range of techniques such as Bayesian methods, neural networks, support vector machines, feature selection and feature reduction techniques.Technical descriptions and motivations are provided, and the techniques are illustrated using real examples.

Statistical Pattern Recognition, 3rd Edition:

- Provides a self-contained introduction to "Statistical Pattern Recognition".
- Includes new material presenting the analysis of complex networks.
- Introduces readers to methods for Bayesian density estimation.
- Presents descriptions of new applications in biometrics, security, finance and condition monitoring.
- Provides descriptions and guidance for implementing techniques, which will be invaluable to software engineers and developers seeking to develop real applications
- Describes mathematically the range of "Statistical Pattern Recognition" techniques.
- Presents a variety of exercises including more extensive computer projects.

The in-depth technical descriptions make Statistical Pattern Recognition suitable for senior undergraduate and graduate students in statistics, computer science and engineering. Statistical Pattern Recognition is also an excellent reference source for technical professionals. Chapters have been arranged to facilitate implementation of the techniques by software engineers and developers in non-statistical engineering fields.

Contents

Preface xix
Notation xxiii

1 Introduction to Statistical Pattern Recognition 1
2 Density Estimation - Parametric 33
3 Density Estimation - Bayesian 70
4 Density Estimation - Nonparametric 150
5 Linear Discriminant Analysis 221
6 Nonlinear Discriminant Analysis - Kernel and Projection Methods 274
7 Rule and Decision Tree Induction 322
8 Ensemble Methods 361
9 Performance Assessment 404
10 Feature Selection and Extraction 433
11 Clustering 501
12 Complex Networks 555
13 Additional Topics 581

References 591
Index 637#

Customer Reviews

Textbook
By: Andrew R Webb(Author), Keith D Copsey(Author)
642 pages, b/w illustrations
Media reviews

"In the end I must add that this book is so appealing that I often found myself lost in the reading, pausing the overview of the manuscript in order to look more into some presented subject, and not being able to continue until I had finished seeing all about it."
- Zentralblatt MATH, 1 December 2012

Current promotions
New and Forthcoming BooksNHBS Moth TrapBritish Wildlife MagazineBuyers Guides