Basu M. (ed.), Ho T.K. (ed.)1-84628-172-5, 9781846281716, 1846281717
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 |
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