Contents 1 Introduction 2 Representation 3 Nearest Neighbour Based Classifiers�4 Bayes Classifier 5 Hidden Markov Models 6 Decision Trees 7 Support Vector Machines 8 Combination of Classifiers 9 Clustering 10 Summary 11 An Application Handwritten Digit Recognition Discussion Further Reading BibliographyObserving the environment and recognising patterns for the purpose of decision making is fundamental to human nature This book deals with the scientific discipline that enables similar perception in machines through pattern recognition which has application in diverse technology areas character recognition image processing industrial automation internet searches speech recognition medical diagnostics target recognition space science remote sensing data mining biometric identification to name a few This book is an exposition of principal topics in pattern recognition using an algorithmic approach It provides a thorough introduction to the concepts of pattern recognition and a systematic account of the major topics in pattern recognition besides reviewing the vast progress made in the field in recent times It includes basic techniques of pattern recognition neural networks support vector machines and decision trees While theoretical aspects have been given due coverage the emphasis is more on the practical The book is replete with examples and illustrations and includes chapter-end exercises 352 pp.

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Bibliographic Details

Title: Pattern Recognition : An Introduction
Publisher: Universities Press
Publication Date: 2011
Language: English
ISBN 10: 8173717257
ISBN 13: 9788173717253
Binding: Soft cover
Condition: New

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