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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
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Title
Multi-Objective Machine Learning
Published by
Springer Science & Business Media, February 2006
DOI 10.1007/3-540-33019-4
ISBNs
978-3-54-030676-4, 978-3-64-206796-9, 978-3-54-033019-6
Editors

Jin, Yaochu

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Croatia 1 3%
Brazil 1 3%
Turkey 1 3%
Colombia 1 3%
Unknown 35 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 31%
Student > Master 7 18%
Researcher 6 15%
Professor > Associate Professor 4 10%
Other 2 5%
Other 8 21%
Readers by discipline Count As %
Computer Science 19 49%
Engineering 11 28%
Unspecified 3 8%
Mathematics 3 8%
Arts and Humanities 1 3%
Other 2 5%