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Band 16

Multi-Objective Machine Learning

Aus der Reihe Studies in Computational Intelligence

197,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

22.11.2010

Abbildungen

XIV, 660 p. 254 illus.

Herausgeber

Yaochu Jin

Verlag

Springer Berlin

Seitenzahl

660

Maße (L/B/H)

23,5/15,5/3,7 cm

Gewicht

1007 g

Auflage

Softcover reprint of hardcover 1st edition 2006

Sprache

Englisch

ISBN

978-3-642-06796-9

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

22.11.2010

Abbildungen

XIV, 660 p. 254 illus.

Herausgeber

Yaochu Jin

Verlag

Springer Berlin

Seitenzahl

660

Maße (L/B/H)

23,5/15,5/3,7 cm

Gewicht

1007 g

Auflage

Softcover reprint of hardcover 1st edition 2006

Sprache

Englisch

ISBN

978-3-642-06796-9

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Multi-Objective Machine Learning
  • Produktbild: Multi-Objective Machine Learning
  • Multi-Objective Clustering, Feature Extraction and Feature Selection.- Feature Selection Using Rough Sets.- Multi-Objective Clustering and Cluster Validation.- Feature Selection for Ensembles Using the Multi-Objective Optimization Approach.- Feature Extraction Using Multi-Objective Genetic Programming.- Multi-Objective Learning for Accuracy Improvement.- Regression Error Characteristic Optimisation of Non-Linear Models.- Regularization for Parameter Identification Using Multi-Objective Optimization.- Multi-Objective Algorithms for Neural Networks Learning.- Generating Support Vector Machines Using Multi-Objective Optimization and Goal Programming.- Multi-Objective Optimization of Support Vector Machines.- Multi-Objective Evolutionary Algorithm for Radial Basis Function Neural Network Design.- Minimizing Structural Risk on Decision Tree Classification.- Multi-objective Learning Classifier Systems.- Multi-Objective Learning for Interpretability Improvement.- Simultaneous Generation of Accurate and Interpretable Neural Network Classifiers.- GA-Based Pareto Optimization for Rule Extraction from Neural Networks.- Agent Based Multi-Objective Approach to Generating Interpretable Fuzzy Systems.- Multi-objective Evolutionary Algorithm for Temporal Linguistic Rule Extraction.- Multiple Objective Learning for Constructing Interpretable Takagi-Sugeno Fuzzy Model.- Multi-Objective Ensemble Generation.- Pareto-Optimal Approaches to Neuro-Ensemble Learning.- Trade-Off Between Diversity and Accuracy in Ensemble Generation.- Cooperative Coevolution of Neural Networks and Ensembles of Neural Networks.- Multi-Objective Structure Selection for RBF Networks and Its Application to Nonlinear System Identification.- Fuzzy Ensemble Design through Multi-Objective Fuzzy Rule Selection.- Applications of Multi-Objective Machine Learning.- Multi-Objective Optimisation for Receiver Operating Characteristic Analysis.- Multi-Objective Design of Neuro-Fuzzy Controllers for Robot Behavior Coordination.- Fuzzy Tuning for the Docking Maneuver Controller of an Automated Guided Vehicle.- A Multi-Objective Genetic Algorithm for Learning Linguistic Persistent Queries in Text Retrieval Environments.- Multi-Objective Neural Network Optimization for Visual Object Detection.