Data Complexity in Pattern Recognition

✍ Scribed by Basu M. (ed.), Ho T.K. (ed.)

• Publisher: Springer
• Year: 2006
• Tongue: English
• Leaves: 306
• Series: Advanced information and knowledge processing
• Category: Library

✦ Synopsis

Machines capable of automatic pattern recognition have many fascinating uses in science & engineering as well as in our daily lives. Algorithms for supervised classification, where one infers a decision boundary from a set of training examples, are at the core of this capability.This book takes a close view of data complexity & its role in shaping the theories & techniques in different disciplines & asks: * What is missing from current classification techniques? * When the automatic classifiers are not perfect, is it a deficiency of the algorithms by design, or is it a difficulty intrinsic to the classification task? * How do we know whether we have exploited to the fullest extent the knowledge embedded in the training data?Uunique in its comprehensive coverage & multidisciplinary approach from various methodological & practical perspectives, researchers & practitioners will find this book an insightful reference to learn about current available techniques as well as application areas.

✦ Table of Contents

front-matter.pdf......Page 1
001-023.pdf......Page 16
025-058.pdf......Page 37
060-068.pdf......Page 71
069-090.pdf......Page 81
091-114.pdf......Page 103
115-134.pdf......Page 127
135-152.pdf......Page 147
153-169.pdf......Page 165
173-195.pdf......Page 182
197-215.pdf......Page 205
217-239.pdf......Page 224
241-248.pdf......Page 247
249-270.pdf......Page 255
271-286.pdf......Page 277
287-298.pdf......Page 293
back-matter.pdf......Page 305