Performance prediction using support vector machine for the configuration of optimization algorithms

The aim of this paper is to propose a machine learning approach for predicting the performance of each configuration of optimization algorithms. Our approach consists of advocating making the decision of finding the most suitable configuration on a per-instance analysis based on a supervised machine...

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Veröffentlicht in:	CloudTech '17 : proceedings of 2017 International Conference of Cloud Computing Technologies and Applications S. 1 - 7
Hauptverfasser:	Afia, Abdellatif El, Sarhani, Malek
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.10.2017
Schlagworte:	Algorithm design and analysis Feature extraction Machine learning algorithms Optimization Prediction algorithms Predictive models Support vector machines
Online-Zugang:	Volltext
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