Items related to Multi-Objective Machine Learning: 16 (Studies in Computation...
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 successful to improve the performance of the traditional single objective machine learning methods, to generate highly diverse multiple Pareto-optimal models for constructing ensembles models and, and to achieve a desired trade-off between accuracy and interpretability of neural networks or fuzzy systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems.
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- PublisherSpringer
- Publication date2006
- ISBN 10 3540306765
- ISBN 13 9783540306764
- BindingHardcover
- Number of pages674
- EditorJin Yaochu
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Multi-Objective Machine Learning (Studies in Computational Intelligence, 16)
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Book Description Condition: New. Selected collection of recent research on multi-objective approach to machine learningRecent developments in evolutionary multi-objective optimizationApplies the concept of Pareto-optimality to machine learning Recently. Seller Inventory # 4887431
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