Improvement of heart attack prediction by the feature selection methods

Takci, Hidayet

Improvement of heart attack prediction by the feature selection methods

Hidayet TAKCI (Cumhuriyet Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Sivas, Türkiye)

Turkish Journal of Electrical Engineering and Computer Sciences

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Yıl: 2018 Cilt: 26 Sayı: 1 Sayfa Aralığı: 1 - 10 Metin Dili: İngilizce İndeks Tarihi: 29-07-2022

Improvement of heart attack prediction by the feature selection methods

Öz:

Prediction of a heart attack is very important since it is one of the leading causes of sudden death, especially in low-income countries. Although cardiologists use traditional clinical methods such as electrocardiography and blood tests for heart attack prediction, computer aided diagnosis systems that use machine learning methods are also in use for this task. In this study, we used machine learning and feature selection algorithms together. Our aim is to determine the best machine learning method and the best feature selection algorithm to predict heart attacks. For this purpose, many machine learning methods with optimum parameters and several feature selection methods were used and evaluated on the Statlog (Heart) dataset. According to the experimental results, the best machine learning algorithm is the support vector machine algorithm with the linear kernel, while the best feature selection algorithm is the reliefF method. This pair gave the highest accuracy value of 84.81%.

Anahtar Kelime:

Konular: Mühendislik, Elektrik ve Elektronik

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık

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APA	Takci H (2018). Improvement of heart attack prediction by the feature selection methods. , 1 - 10.
Chicago	Takci Hidayet Improvement of heart attack prediction by the feature selection methods. (2018): 1 - 10.
MLA	Takci Hidayet Improvement of heart attack prediction by the feature selection methods. , 2018, ss.1 - 10.
AMA	Takci H Improvement of heart attack prediction by the feature selection methods. . 2018; 1 - 10.
Vancouver	Takci H Improvement of heart attack prediction by the feature selection methods. . 2018; 1 - 10.
IEEE	Takci H "Improvement of heart attack prediction by the feature selection methods." , ss.1 - 10, 2018.
ISNAD	Takci, Hidayet. "Improvement of heart attack prediction by the feature selection methods". (2018), 1-10.

APA	Takci H (2018). Improvement of heart attack prediction by the feature selection methods. Turkish Journal of Electrical Engineering and Computer Sciences, 26(1), 1 - 10.
Chicago	Takci Hidayet Improvement of heart attack prediction by the feature selection methods. Turkish Journal of Electrical Engineering and Computer Sciences 26, no.1 (2018): 1 - 10.
MLA	Takci Hidayet Improvement of heart attack prediction by the feature selection methods. Turkish Journal of Electrical Engineering and Computer Sciences, vol.26, no.1, 2018, ss.1 - 10.
AMA	Takci H Improvement of heart attack prediction by the feature selection methods. Turkish Journal of Electrical Engineering and Computer Sciences. 2018; 26(1): 1 - 10.
Vancouver	Takci H Improvement of heart attack prediction by the feature selection methods. Turkish Journal of Electrical Engineering and Computer Sciences. 2018; 26(1): 1 - 10.
IEEE	Takci H "Improvement of heart attack prediction by the feature selection methods." Turkish Journal of Electrical Engineering and Computer Sciences, 26, ss.1 - 10, 2018.
ISNAD	Takci, Hidayet. "Improvement of heart attack prediction by the feature selection methods". Turkish Journal of Electrical Engineering and Computer Sciences 26/1 (2018), 1-10.