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Cardiac Arrhythmia Classification Using KNN and Naive Bayes Classifiers Optimized with Differential Evolution (DE) and Particle Swarm Optimization (PSO)
Christian Padilla-Navarro, Rosario Baltazar-Flores, David Cuesta-Frau, Arnulfo Alanis-Garza, Victor Zamudio-Rodríguez
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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