TY - RPRT U1 - Forschungsbericht A1 - Bartz-Beielstein, Thomas T1 - Stacked Generalization of Surrogate Models - A Practical Approach N2 - 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. T3 - CIplus - 5/2016 KW - Metamodell KW - Optimierung KW - Surrogate Model KW - Stacked Generalization KW - Ensemble based modeling KW - Sequential Parameter Optimization Y2 - 2016 U6 - https://nbn-resolving.org/urn:nbn:de:hbz:832-cos4-3759 UN - https://nbn-resolving.org/urn:nbn:de:hbz:832-cos4-3759 SP - 20 S1 - 20 ER -