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Comparing Performance of Data Mining Algorithms in Prediction Heart Diseses Publisher



Abdar M1 ; Kalhori SRN2 ; Sutikno T3 ; Subroto IMI4 ; Arji G5
Authors

Source: International Journal of Electrical and Computer Engineering Published:2015


Abstract

Heart diseases are among the nation's leading couse of mortality and moribidity. Data mining teqniques can predict the likelihood of patients getting a heart disease. The purpose of this study is comparison of different data mining algorithm on prediction of heart diseases. This work applied and compared data mining techniques to predict the risk of heart diseases.After feature analysis, models by six algorithms including decision tree, neural network, support vector machine and k-nearest neighborhood developed and validated. C5.0 Decision tree has been able to build a model with greatest accuracy 93.02%, KNN, SVM, Neural network have been 88.37%, 86.05% and 80.23% respectively. Produced results of decision tree can be simply interpretable and applicable; their rules can be understood easily by different clinical practitioner. © 2015 Institute of Advanced Engineering and Science. All rights reserved.
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