Theory and Methodology.- Measures of Geometrical Complexity in Classification Problems.- Object Representation, Sample Size and Dataset 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.- Data Complexity and Domains of Competence of Classifiers.- Data Complexity Issues in Grammatical Inference.- Applications.- Simple Statistics for Complex Feature Spaces.- Polynomial Time for Complexity Graph Distance Computation for Web Content Mining.- Data Complexity in Clustering Analysis for 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.
EAN/ISBN : 9781846281723
Publisher(s): Springer, Berlin, Springer, London
Discussed keywords: Mustererkennung
Format: ePub/PDF

Author(s): Basu, Mitra - Ho, Tin Kam