Table 6.

Performance of different machine learning methods on 2D, 3D and fingerprints collectively.

	Parameters	Main dataset					Validation dataset
		Sen	Spc	Acc	MCC	AUROC	Sen	Spc	Acc	MCC	AUROC
SVM	g = 1e-05, c = 15, j = 1	83.33	79.21	81.27	0.63	0.89	78.67	82.67	80.67	0.61	0.87
Random Forest	Ntree = 60	95.19	95.02	95.10	0.90	0.99	91.33	93.33	92.33	0.85	0.98
SMO	g = 0.0001, c = 5	76.80	76.98	76.89	0.54	0.76	75.33	83.33	79.33	0.59	0.79
J48	c = 0.25, m = 5	89.69	87.63	88.66	0.77	0.90	84.67	92.00	88.33	0.77	0.92
Naive Bayes	Default	95.19	88.14	91.67	0.84	0.95	92.00	89.33	90.67	0.81	0.96