Table 2.

Classification results with the unbalanced dataset

		ZR	KNN	SVM	NB	RBF	J48	RF
All features	Accuracy	0.636	0.763	0.773	0.703	0.691	0.753	0.800
	Sensitivity	0.000	0.596	0.493	0.244	0.209	0.617	0.702
	Specificity	1.000	0.859	0.933	0.965	0.966	0.831	0.856
	AUC	0.496	0.827	0.713	0.769	0.695	0.735	0.858
Features	Accuracy	0.636	0.756	0.774	0.702	0.683	0.762	0.786
selected by	Sensitivity	0.000	0.563	0.491	0.242	0.350	0.636	0.685
statistics	Specificity	1.000	0.866	0.936	0.965	0.874	0.834	0.843
	AUC	0.496	0.794	0.713	0.749	0.702	0.747	0.847
Features	Accuracy	0.636	0.766	0.765	0.703	0.740	0.777	0.781
selected by	Sensitivity	0.000	0.559	0.495	0.223	0.392	0.650	0.655
correlation	Specificity	1.000	0.885	0.919	0.977	0.940	0.850	0.854
	AUC	0.496	0.811	0.707	0.778	0.709	0.771	0.846
Features	Accuracy	0.636	0.792	0.784	0.769	0.761	0.786	0.788
selected by	Sensitivity	0.000	0.664	0.531	0.502	0.505	0.575	0.662
wrapper	Specificity	1.000	0.866	0.929	0.921	0.907	0.906	0.860
	AUC	0.496	0.816	0.730	0.792	0.752	0.710	0.843

Italicized values are the highest for each row