We apply an automatic tuning method for the hyperparameters of a SVM classifier. The data used to train and test the algorithm come from industrial measurements made on the products after being built up. Various training sessions have been carried on in different learning environments and the results have been validated through a bootstrap techníque. We discuss the obtained results and show the good adaptability of the method.
Automatic Hyperparameters Adaptation in Support Vector Machines
ANGUITA, DAVIDE;
2002-01-01
Abstract
We apply an automatic tuning method for the hyperparameters of a SVM classifier. The data used to train and test the algorithm come from industrial measurements made on the products after being built up. Various training sessions have been carried on in different learning environments and the results have been validated through a bootstrap techníque. We discuss the obtained results and show the good adaptability of the method.
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