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Multi-Objective Machine Learning

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Cover of 'Multi-Objective Machine Learning'

Table of Contents

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    Book Overview
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    Chapter 1 Feature Selection Using Rough Sets
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    Chapter 2 Multi-Objective Clustering and Cluster Validation
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    Chapter 3 Feature Selection for Ensembles Using the Multi-Objective Optimization Approach
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    Chapter 4 Feature Extraction Using Multi-Objective Genetic Programming
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    Chapter 5 Multi-Objective Machine Learning
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    Chapter 6 Regularization for Parameter Identification Using Multi-Objective Optimization
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    Chapter 7 Multi-Objective Algorithms for Neural Networks Learning
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    Chapter 8 Generating Support Vector Machines Using Multi-Objective Optimization and Goal Programming
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    Chapter 9 Multi-Objective Optimization of Support Vector Machines
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    Chapter 10 Multi-Objective Evolutionary Algorithm for Radial Basis Function Neural Network Design
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    Chapter 11 Minimizing Structural Risk on Decision Tree Classification
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    Chapter 12 Multi-objective Learning Classifier Systems
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    Chapter 13 Simultaneous Generation of Accurate and Interpretable Neural Network Classifiers
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    Chapter 14 GA-Based Pareto Optimization for Rule Extraction from Neural Networks
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    Chapter 15 Agent Based Multi-Objective Approach to Generating Interpretable Fuzzy Systems
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    Chapter 16 Multi-objective Evolutionary Algorithm for Temporal Linguistic Rule Extraction
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    Chapter 17 Multiple Objective Learning for Constructing Interpretable Takagi-Sugeno Fuzzy Model
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    Chapter 18 Multi-Objective Machine Learning
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    Chapter 19 Trade-Off Between Diversity and Accuracy in Ensemble Generation
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    Chapter 20 Cooperative Coevolution of Neural Networks and Ensembles of Neural Networks
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    Chapter 21 Multi-Objective Structure Selection for RBF Networks and Its Application to Nonlinear System Identification
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    Chapter 22 Fuzzy Ensemble Design through Multi-Objective Fuzzy Rule Selection
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    Chapter 23 Multi-Objective Machine Learning
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    Chapter 24 Multi-Objective Design of Neuro-Fuzzy Controllers for Robot Behavior Coordination
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    Chapter 25 Fuzzy Tuning for the Docking Maneuver Controller of an Automated Guided Vehicle
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    Chapter 26 A Multi-Objective Genetic Algorithm for Learning Linguistic Persistent Queries in Text Retrieval Environments
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    Chapter 27 Multi-Objective Neural Network Optimization for Visual Object Detection
Attention for Chapter 23: Multi-Objective Machine Learning
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Chapter title
Multi-Objective Machine Learning
Chapter number 23
Book title
Multi-Objective Machine Learning
Published by
Springer Nature, January 2006
DOI 10.1007/3-540-33019-4_23
Book ISBNs
978-3-54-030676-4, 978-3-54-033019-6
Authors

Richard M. Everson, Jonathan E. Fieldsend, Everson, Richard M., Fieldsend, Jonathan E.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 2 22%
Lecturer 1 11%
Student > Doctoral Student 1 11%
Student > Ph. D. Student 1 11%
Professor 1 11%
Other 2 22%
Unknown 1 11%
Readers by discipline Count As %
Computer Science 6 67%
Energy 1 11%
Unknown 2 22%