In the present investigation we are looking for improve the features classification of a cardiac arrhythmias database using metaheuristics (Differential Evolution and Particle Swarm Optimization) and classifiers (KNN and Naive Bayes), with the purpose of select the main features and increase the percentage of classification. The classification percentage in some cases increased until 100% and the number of features was significantly reduced.
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