A Study on Performance Improvement of Heart Disease Prediction by Attribute Selection Methods

Year 2019, Volume: 7 Issue: 2, 174 - 179, 25.05.2019

Kemal Akyol , Ümit Atila

Abstract

Heart pumps blood for all tissues of the body. The deteriorate of this organ causes a severe illness, disability and death since
cardiovascular diseases involve the diseases that related to heart and circulation system. Determination of the significance of
factors affecting this disease is of great importance for early prevention and treatment of this disease. In this study, firstly, the
best attributes set for Single Proton Emission Computed Tomography (SPECT) and Statlog Heart Disease (STATLOG) datasets
were detected by using feature selection methods named RFECV (Recursive Feature Elimination with cross-validation) and SS
(Stability Selection). Secondly, GBM (Gradient Boosted Machines), NB (Naive Bayes) and RF (Random Forest) algorithms
were implemented with original datasets and with datasets having selected attributes by RFECV and SS methods and their
performances were compared for each dataset. The experimental results showed that maximum performance increases were
obtained on SPECT dataset by 14.81% when GBM algorithm was applied using attributes provided by RFECV method and on
STATLOG dataset by 6.18% when GBM algorithm was applied using attributes provided by RFECV method. On the other hand,
best accuracies were obtained by NB algorithm when applied using attributes of SPECT dataset provided by RFECV method
and using attributes of STATLOG dataset provided by SS method. The results showed that medical decision support systems
which can make more accurate predictions could be developed using enhanced machine learning methods by RFECV and SS
methods and this can be helpful in selecting the treatment method for the experts in the field.

Keywords

Cardiovascular disease, attribute importance, attribute selection, stability selection, recursive feature selection

Öznitelik Seçimi Algoritmaları Kullanılarak Kalp Hastalığı Tahmininin Performans İyileştirmesi Üzerine Bir Çalışma

Abstract

Keywords

Kardiyovasküler hastalık, özniteliğin önemi, öznitelik seçimi, kararlılık seçimi, özyinelemeli özellik seçimi

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