Discriminant Analysis and Statistical Pattern Recognition
Title | Discriminant Analysis and Statistical Pattern Recognition PDF eBook |
Author | Geoffrey McLachlan |
Publisher | John Wiley & Sons |
Pages | 526 |
Release | 2005-02-25 |
Genre | Mathematics |
ISBN | 0471725285 |
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "For both applied and theoretical statisticians as well as investigators working in the many areas in which relevant use can be made of discriminant techniques, this monograph provides a modern, comprehensive, and systematic account of discriminant analysis, with the focus on the more recent advances in the field." –SciTech Book News ". . . a very useful source of information for any researcher working in discriminant analysis and pattern recognition." –Computational Statistics Discriminant Analysis and Statistical Pattern Recognition provides a systematic account of the subject. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are regularized discriminant analysis and bootstrap-based assessment of the performance of a sample-based discriminant rule, and extensions of discriminant analysis motivated by problems in statistical image analysis. The accompanying bibliography contains over 1,200 references.
Statistical Pattern Recognition
Title | Statistical Pattern Recognition PDF eBook |
Author | Andrew R. Webb |
Publisher | John Wiley & Sons |
Pages | 516 |
Release | 2003-07-25 |
Genre | Mathematics |
ISBN | 0470854782 |
Statistical pattern recognition is a very active area of study andresearch, which has seen many advances in recent years. New andemerging applications - such as data mining, web searching,multimedia data retrieval, face recognition, and cursivehandwriting recognition - require robust and efficient patternrecognition techniques. Statistical decision making and estimationare regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fullyupdated with new methods, applications and references. It providesa comprehensive introduction to this vibrant area - with materialdrawn from engineering, statistics, computer science and the socialsciences - and covers many application areas, such as databasedesign, artificial neural networks, and decision supportsystems. * Provides a self-contained introduction to statistical patternrecognition. * Each technique described is illustrated by real examples. * Covers Bayesian methods, neural networks, support vectormachines, and unsupervised classification. * Each section concludes with a description of the applicationsthat have been addressed and with further developments of thetheory. * Includes background material on dissimilarity, parameterestimation, data, linear algebra and probability. * Features a variety of exercises, from 'open-book' questions tomore lengthy projects. The book is aimed primarily at senior undergraduate and graduatestudents studying statistical pattern recognition, patternprocessing, neural networks, and data mining, in both statisticsand engineering departments. It is also an excellent source ofreference for technical professionals working in advancedinformation development environments. For further information on the techniques and applicationsdiscussed in this book please visit ahref="http://www.statistical-pattern-recognition.net/"www.statistical-pattern-recognition.net/a
Discriminant Analysis and Statistical Pattern Recognition
Title | Discriminant Analysis and Statistical Pattern Recognition PDF eBook |
Author | Geoffrey McLachlan |
Publisher | Wiley-Interscience |
Pages | 556 |
Release | 1992-04-10 |
Genre | Computers |
ISBN |
Reflecting also the increasingly image-based nature of data, especially in remote sensing, the book outlines extensions of discriminant analysis motivated by problems in statistical image analysis." "The sequence of chapters is clearly and logically developed, beginning with a general introduction to discriminant analysis in Chapter 1.
Introduction to Statistical Pattern Recognition
Title | Introduction to Statistical Pattern Recognition PDF eBook |
Author | Keinosuke Fukunaga |
Publisher | Elsevier |
Pages | 606 |
Release | 2013-10-22 |
Genre | Computers |
ISBN | 0080478654 |
This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises.
Discriminant Analysis and Statistical Pattern Recognition
Title | Discriminant Analysis and Statistical Pattern Recognition PDF eBook |
Author | Geoffrey J. McLachlan |
Publisher | John Wiley & Sons |
Pages | 552 |
Release | 2005-02-25 |
Genre | Mathematics |
ISBN | 0471725285 |
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "For both applied and theoretical statisticians as well as investigators working in the many areas in which relevant use can be made of discriminant techniques, this monograph provides a modern, comprehensive, and systematic account of discriminant analysis, with the focus on the more recent advances in the field." –SciTech Book News ". . . a very useful source of information for any researcher working in discriminant analysis and pattern recognition." –Computational Statistics Discriminant Analysis and Statistical Pattern Recognition provides a systematic account of the subject. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are regularized discriminant analysis and bootstrap-based assessment of the performance of a sample-based discriminant rule, and extensions of discriminant analysis motivated by problems in statistical image analysis. The accompanying bibliography contains over 1,200 references.
Pattern Recognition and Neural Networks
Title | Pattern Recognition and Neural Networks PDF eBook |
Author | Brian D. Ripley |
Publisher | Cambridge University Press |
Pages | 420 |
Release | 2007 |
Genre | Computers |
ISBN | 9780521717700 |
This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.
Statistical and Neural Classifiers
Title | Statistical and Neural Classifiers PDF eBook |
Author | Sarunas Raudys |
Publisher | Springer Science & Business Media |
Pages | 328 |
Release | 2001-01-29 |
Genre | Computers |
ISBN | 9781852332976 |
The classification of patterns is an important area of research which is central to all pattern recognition fields, including speech, image, robotics, and data analysis. Neural networks have been used successfully in a number of these fields, but so far their application has been based on a 'black box approach' with no real understanding of how they work. In this book, Sarunas Raudys - an internationally respected researcher in the area - provides an excellent mathematical and applied introduction to how neural network classifiers work and how they should be used.. .