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Data Complexity in Pattern Recognition

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Cover of 'Data Complexity in Pattern Recognition'

Table of Contents

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    Book Overview
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    Chapter 1 Measures of Geometrical Complexity in Classification Problems
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    Chapter 2 Object Representation, Sample Size, and Data Set Complexity
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    Chapter 3 Measures of Data and Classifier Complexity and the Training Sample Size
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    Chapter 4 Linear Separability in Descent Procedures for Linear Classifiers
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    Chapter 5 Data Complexity, Margin-Based Learning, and Popper’s Philosophy of Inductive Learning
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    Chapter 6 Data Complexity and Evolutionary Learning
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    Chapter 7 Classifier Domains of Competence in Data Complexity Space
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    Chapter 8 Data Complexity Issues in Grammatical Inference
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    Chapter 9 Simple Statistics for Complex Feature Spaces
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    Chapter 10 Polynomial Time Complexity Graph Distance Computation for Web Content Mining
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    Chapter 11 Data Complexity in Clustering Analysis of Gene Microarray Expression Profiles
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    Chapter 12 Complexity of Magnetic Resonance Spectrum Classification
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    Chapter 13 Data Complexity in Tropical Cyclone Positioning and Classification
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    Chapter 14 Human-Computer Interaction for Complex Pattern Recognition Problems
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    Chapter 15 Complex Image Recognition and Web Security
Attention for Chapter 5: Data Complexity, Margin-Based Learning, and Popper’s Philosophy of Inductive Learning
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