Instead, this paper proposes a multi-objective approach can benefit the domain expert since it enables automatic model type selection for each output on the fly ...
Instead, this paper proposes a multi-objective approach can benefit the domain expert since it enables automatic model type selection for each output on the fly ...
When applying surrogate models to multi-output systems, the hyperparameter optimization problem is typically formulated in a single objective way. The different ...
Popular surrogate model types include neural networks, support vector machines, and splines. In addition, the cost of each simulation mandates the use of active ...
Pareto-Based Multi-output Metamodeling with Active Learning
www.researchgate.net › ... › Metamodeling
... A Pareto based approach to multi-output modeling also allows integration with the automatic surrogate model type selection algorithm described in [39]. This ...
Popular surrogate model types include neural networks, support vector machines, Kriging models, and splines. An engineering simulation typically involves ...
Instead, this paper proposes a multi-objective approach can benefit the domain expert since it enables automatic model type selection for each output on the fly ...
ParetoCluster is an effective multi-label feature selection algorithm based on Pareto dominance and cluster analysis concepts which considers each label an ...
Popular surrogate model types include neural networks, support vector machines, and splines. In addition, the cost of each simulation mandates the use of active ...
When applying surrogate models to multi-output systems, the hyperparameter optimization problem is typically formulated in a single objective way. The different ...