A Comparative Study of Medical Data Classification Methods Based on Decision Tree and Bagging Algorithms

Medical data mining has been a popular data mining topic of late. Especially, diagnosing of the heart disease is one of the important issue and many researchers investigated to develop intelligent medical decision support systems to help the physicians. In this paper, we propose the use of decision tree C4.5 algorithm, bagging with decision tree C4.5 algorithm and bagging with Nai¿ve Bayes algorithm to identify the heart disease of a patient and compare the effectiveness, correction rate among them. The data we study is collected from patients with coronary artery disease.