Using decision tree for diagnosing heart disease patients

摘要: Heart disease is the leading cause of death in world over past 10 years. Researchers have been using several data mining techniques to help health care professionals diagnosis heart disease. Decision Tree one successful used. However, most research has applied J4.8 Tree, based on Gain Ratio and binary discretization. Gini Index Information are two other types Trees that less used Also discretization techniques, voting method, reduced error pruning known produce more accurate Trees. This investigates applying a range different seeking better performance diagnosis. A widely benchmark set this research. To evaluate alternative sensitivity, specificity, accuracy calculated. The proposes model outperforms Bagging algorithm patients.