Multi-Objective Machine Learning
Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly su...
Salvato in:
| Altri autori: | |
|---|---|
| Natura: | Livre numérique |
| Lingua: | Anglais |
| Pubblicazione: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edizione: | 1st ed. 2006. |
| Serie: | Studies in Computational Intelligence
16 |
| Accesso online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Multi-objective machine learning, Yaochu Jin (ed.), Berlin, Springer, 2006, 1 vol. (xiii, 660 p.), Studies in computational intelligence, 3-540-30676-5 • Multi-Objective Machine Learning, Texte imprimé, 9783642067969 • Multi-Objective Machine Learning, Texte imprimé, 9783540818359 • Multi-objective machine learning, Yaochu Jin (ed.), Berlin, Springer, 2006, 1 vol. (xiii, 660 p.), Studies in computational intelligence, 3-540-30676-5 |
Sommario:
- 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