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 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…
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Produktdetails
- ISBN: 978-3-540-30676-4
- EAN: 9783540306764
- Produktnummer: 2144385
- Verlag: Springer-Verlag GmbH
- Sprache: Englisch
- Erscheinungsjahr: 2006
- Seitenangabe: 660 S.
- Masse: H24.1 cm x B16.3 cm x D4.3 cm 1'173 g
- Auflage: 2006. 2006
- Abbildungen: Book; 254 schwarz-weiße Abbildungen, 104 schwarz-weiße Tabellen, Bibliographie
- Reihenbandnummer: 16
- Gewicht: 1173
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