Data Complexity in Pattern Recognition
Springer London Ltd (Verlag)
978-1-84996-557-6 (ISBN)
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 | 22.10.2010 |
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Reihe/Serie | Advanced Information and Knowledge Processing |
Zusatzinfo | XVI, 300 p. |
Verlagsort | England |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Informatik ► Theorie / Studium ► Algorithmen |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
ISBN-10 | 1-84996-557-9 / 1849965579 |
ISBN-13 | 978-1-84996-557-6 / 9781849965576 |
Zustand | Neuware |
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