Classification of ECG Signal by using Machine Learning Methods

dc.contributor.author	Diker, Aykut
dc.contributor.author	Avci, Engin
dc.contributor.author	Comert, Zafer
dc.contributor.author	Avci, Derya
dc.contributor.author	Kacar, Emine
dc.contributor.author	Serhatlioglu, Ihsan
dc.date.accessioned	2021-12-16T09:07:20Z
dc.date.available	2021-12-16T09:07:20Z
dc.date.issued	2018
dc.identifier.isbn	978-1-5386-1501-0
dc.identifier.issn	2165-0608
dc.identifier.uri	http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/10322
dc.description.abstract	In this study, an application of Artificial Neural Networks (ANN), Support Vector Machines (SVM), and k-Nearest Neighbor (k-NN) machine learning methods is performed to measure the classification performance of the models on classifying electrocardiogram
dc.language.iso	Turkish
dc.publisher	Ieee
dc.relation.ispartof	26th IEEE Signal Processing and Communications Applications Conference (SIU)
dc.source	2018 26Th Sıgnal Processıng And Communıcatıons Applıcatıons Conference (Sıu)
dc.title	Classification of ECG Signal by using Machine Learning Methods
dc.type	Proceedings Paper
dc.identifier.wos	WOS:000511448500151

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