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Computational Intelligence Paradigms

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Cover of 'Computational Intelligence Paradigms'

Table of Contents

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    Book Overview
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    Chapter 1 Computational Intelligence Paradigms
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    Chapter 2 A Quest for Adaptable and Interpretable Architectures of Computational Intelligence
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    Chapter 3 MembershipMap: A Data Transformation for Knowledge Discovery Based on Granulation and Fuzzy Membership Aggregation
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    Chapter 4 Advanced Developments and Applications of the Fuzzy ARTMAP Neural Network in Pattern Classification
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    Chapter 5 Large Margin Methods for Structured Output Prediction
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    Chapter 6 Ensemble MLP Classifier Design
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    Chapter 7 Functional Principal Points and Functional Cluster Analysis
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    Chapter 8 Clustering with Size Constraints
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    Chapter 9 Cluster Validating Techniques in the Presence of Duplicates
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    Chapter 10 Fuzzy Blocking Regression Models
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    Chapter 11 Support Vector Machines and Features for Environment Perception in Mobile Robotics
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    Chapter 12 Linkage Analysis in Genetic Algorithms
Attention for Chapter 5: Large Margin Methods for Structured Output Prediction
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Summary
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Chapter title
Large Margin Methods for Structured Output Prediction
Chapter number 5
Book title
Computational Intelligence Paradigms
Published by
Springer, Berlin, Heidelberg, January 2008
DOI 10.1007/978-3-540-79474-5_5
Book ISBNs
978-3-54-079473-8, 978-3-54-079474-5
Authors

Elisa Ricci, Renzo Perfetti

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