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Data Complexity in Pattern Recognition -

Data Complexity in Pattern Recognition

Mitra Basu, Tin Kam Ho (Herausgeber)

Buch | Hardcover
300 Seiten
2006
Springer London Ltd (Verlag)
978-1-84628-171-6 (ISBN)
CHF 224,65 inkl. MwSt
Examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of classification techniques, and the algorithms that drive them. This title offers guidance on choosing pattern recognition classification techniques, helps the reader set expectations for classification performance.
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.

Theory and Methodology.- Measures of Geometrical Complexity in Classification Problems.- Object Representation, Sample Size, and Data Set Complexity.- Measures of Data and Classifier Complexity and the Training Sample Size.- Linear Separability in Descent Procedures for Linear Classifiers.- Data Complexity, Margin-Based Learning, and Popper’s Philosophy of Inductive Learning.- Data Complexity and Evolutionary Learning.- Classifier Domains of Competence in Data Complexity Space.- Data Complexity Issues in Grammatical Inference.- Applications.- Simple Statistics for Complex Feature Spaces.- Polynomial Time Complexity Graph Distance Computation for Web Content Mining.- Data Complexity in Clustering Analysis of Gene Microarray Expression Profiles.- Complexity of Magnetic Resonance Spectrum Classification.- Data Complexity in Tropical Cyclone Positioning and Classification.- Human-Computer Interaction for Complex Pattern Recognition Problems.- Complex Image Recognition and Web Security.

Erscheint lt. Verlag 17.10.2006
Reihe/Serie Advanced Information and Knowledge Processing
Zusatzinfo XVI, 300 p.
Verlagsort England
Sprache englisch
Maße 156 x 235 mm
Themenwelt Informatik Theorie / Studium Algorithmen
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
ISBN-10 1-84628-171-7 / 1846281717
ISBN-13 978-1-84628-171-6 / 9781846281716
Zustand Neuware
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