Feature selection for ECG beat classification using genetic algorithms with a multi-objective approach [Çok Amaçli Yaklasimla Genetik Algoritmalar Kullanarak EKG Vuru Siniflandirmasi için Öznitelik Seçimi]

dc.contributor.author	Sarvan, C.
dc.contributor.author	Ozkurt, N.
dc.date.accessioned	2021-01-25T20:48:32Z
dc.date.available	2021-01-25T20:48:32Z
dc.date.issued	2018
dc.identifier	10.1109/SIU.2018.8404423
dc.identifier.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050810212&doi=10.1109%2fSIU.2018.8404423&partnerID=40&md5=014ea72760f383e58fa0c02db059120a
dc.identifier.uri	https://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/9957
dc.description.abstract	To identify appropriate features in classification studies is a common problem in many areas. In this study, a genetic algorithm method with multi-objective approach is proposed for selecting the features that give high performance ratio in classifying ca
dc.language.iso	English
dc.publisher	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
dc.title	Feature selection for ECG beat classification using genetic algorithms with a multi-objective approach [Çok Amaçli Yaklasimla Genetik Algoritmalar Kullanarak EKG Vuru Siniflandirmasi için Öznitelik Seçimi]
dc.type	Conference Paper
dc.relation.firstpage	1
dc.relation.lastpage	4
dc.description.affiliations	Elektrik Ve Elektronik Muhendisliǧi Bolumu, Yaşar Universitesi, Izmir, Turkey

Bu öğenin dosyaları:

Dosyalar	Boyut	Biçim	Göster
Bu öğe ile ilişkili dosya yok.