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…
Mehr
CHF 308.50
Preise inkl. MwSt. und Versandkosten (Portofrei ab CHF 40.00)
Versandkostenfrei
Produktdetails
- ISBN: 978-3-540-33019-6
- EAN: 9783540330196
- Produktnummer: 33325578
- Verlag: Springer-Verlag GmbH
- Sprache: Englisch
- Erscheinungsjahr: 2007
- Seitenangabe: 660 S.
- Plattform: PDF
- Masse: 16'316 KB
- Auflage: 2006
- Abbildungen: 254 schwarz-weiße Abbildungen, 104 schwarz-weiße Tabellen, Bibliographie
- Reihenbandnummer: 16
28 weitere Werke von Yaochu (Hrsg.) Jin:
Bewertungen
Anmelden