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Stacked Generalization of Surrogate Models - A Practical Approach

  • This report presents a practical approach to stacked generalization in surrogate model based optimization. It exemplifies the integration of stacking methods into the surrogate model building process. First, a brief overview of the current state in surrogate model based opti- mization is presented. Stacked generalization is introduced as a promising ensemble surrogate modeling approach. Then two examples (the first is based on a real world application and the second on a set of artificial test functions) are presented. These examples clearly illustrate two properties of stacked generalization: (i) combining information from two poor performing models can result in a good performing model and (ii) even if the ensemble contains a good performing model, combining its information with information from poor performing models results in a relatively small performance decrease only.

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Author:Thomas Bartz-BeielsteinGND
Series (Serial Number):CIplus (5/2016)
Document Type:Report
Year of Completion:2016
Release Date:2016/06/09
Tag:Ensemble based modeling; Sequential Parameter Optimization; Stacked Generalization; Surrogate Model
GND Keyword:Metamodell; Optimierung
Institutes and Central Facilities:Fakultät für Informatik und Ingenieurwissenschaften (F10)
CCS-Classification:G. Mathematics of Computing / G.0 GENERAL
J. Computer Applications / J.2 PHYSICAL SCIENCES AND ENGINEERING / Mathematics and statistics
Dewey Decimal Classification:500 Naturwissenschaften und Mathematik / 510 Mathematik
000 Allgemeines, Informatik, Informationswissenschaft / 000 Allgemeines, Wissenschaft / 004 Informatik
JEL-Classification:C Mathematical and Quantitative Methods / C6 Mathematical Methods and Programming / C61 Optimization Techniques; Programming Models; Dynamic Analysis
C Mathematical and Quantitative Methods / C8 Data Collection and Data Estimation Methodology; Computer Programs / C89 Other
C Mathematical and Quantitative Methods / C9 Design of Experiments / C90 General
Open Access:Open Access
Licence (German):License LogoCreative Commons - Namensnennung, Nicht kommerziell, Keine Bearbeitung