Engineering Sciences

Yazarlar: Yunus KÖKVER, Necaattin BARIŞÇI, Aydın ÇİFTÇİ, Yakup EKMEKÇİ

Konular:-

DOI:10.12739/NWSA.2014.9.2.1A0352

Anahtar Kelimeler:Hypertension,Data Mining,C4.5,Multilayer Perceptron,Naive Bayes

Özet: In this paper, Age, Gender, Body Mass Index, HDL, LDL, Triglyceride, Uric Acid and The Use of Smoking data gathered from 150 patients are analyzed with data mining classification algorithms. The data is divided into two different classes which are normal and patient. Thus, a diagnostic system is developed which predicts whether a candidate patient has hypertension or not. Besides, a decision tree is created and factors affecting hypertension directly and indirectly are determined. In this study, C4.5, Naive Bayes and Multilayer perceptron classification algorithms are used, and shown that C4.5 algorithm gives better results.

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