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This method is based on a wrapper algorithm with a sequential search strategy.
This method is based on a wrapper approach with a complete search strategy for subset channel selection.
Then, an 11-dimensional feature vector is selected based on a wrapper feature selection algorithm and a support vector machine (SVM).
The proposed evaluator is based on a wrapper approach that utilises two performance measures (MCC and AUC) in conjunction with the k-Nearest Neighbours classification model (kNN).
Our feature selection is based on a wrapper method that uses a genetic algorithm (GA) and an Artificial Neural Network (ANN).
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Based on group 8 of the real database that generated the highest average and lowest standard deviation of the correlation, a wrapper, based on a binary genetic algorithm (GA) with fitness given by the cross-validation MSE is applied to a second selection of markers.
Wrapper methods based on backward feature elimination, such as SVM-RFE (Guyon et al., 2002), are limited in choosing a small set of highly discriminative features.
With their John Lewis store in Leicester Moussavi and Zaera-Polo addressed the nature of modern retail architecture – that it is about big boxes with fancy skins – and made a virtue out it, with a dazzling wrapper based on a 200-year-old linen pattern.
Our initial guess of such a Wrapper algorithm was based on a previous finding [17] that the coverage of the target can be increased with several, successive fast BD cycles where accumulated docked ligand copies from the previous cycle are considered as part of the target in the next cycle.
It is based on a network model interface, a software wrapper that abstracts the interaction between a generic component and a generic framework.
Best attributes for the models were selected based on a supervised attribute selection method called wrapper subset evaluator (WSE).
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