Application of Differential Evolution for Optimization of Least-Square Support Vector Machine Classifier of Signal-Averaged Electrocardiograms
2009
This paper presents the application of differential evolution, an evolutionary algorithm of solving a single objective
optimization problem - tuning the hiperparameters of least-square support vector machine classifier. The goal was to
improve the classification of patients with sustained ventricular tachycardia after myocardial infarction based on a
signal-averaged electrocardiography dataset received from the Medical University of Warsaw. The applied method
attained a classification rate of 96% of the SVT+ group.
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