Table 3.

Performance comparison among machine learning algorithms

Method	Sensitivity	Specificity	F-Measure	Accuracy	AUC
CART	0.813	0.807	0.811	0.810	0.855
Naive Bayesian	0.589	0.893	0.710	0.743	0.811
BayesianNet	0.604	0.914	0.727	0.760	0.839
J48	0.858	0.843	0.850	0.850	0.892
Logistic	0.628	0.893	0.738	0.762	0.845
Neural Network	0.659	0.849	0.742	0.754	0.833
SVM	0.565	0.902	0.695	0.735	0.734