Table 2. AUC and standard deviation (SD) of ensemble learning (EL) in 11 groups of weights for NI and RBM based on dataset of DrugVirus, MDAD and aBiofilm.

Bolded values indicate the best result in 11 groups of results.

Datasets	EL	The	11	Groups	Weights
	groups	1	2	3	4	5	6	7	8	9	10	11
	NI	1	0.9	0.8	0.7	0.6	0.5	0.4	0.3	0.2	0.1	0
	RBM	0	0.1	0.2	0.3	0.4	0.5	0.6	0.7	0.8	0.9	1
DrugVirus	AUC	0.8282	0.8464	0.8540	0.8568	0.8569	0.8552	0.8521	0.8521	0.8478	0.8424	0.8261
	SD	0.0040	0.0032	0.0029	0.0027	0.0027	0.0026	0.0027	0.0027	0.0027	0.0028	0.0035
MDAD	AUC	0.9169	0.9246	0.9248	0.9239	0.9226	0.9209	0.9190	0.9167	0.9139	0.9099	0.9021
	SD	0.0018	0.0015	0.0014	0.0014	0.0013	0.0013	0.0012	0.0012	0.0011	0.0011	0.0012
aBiofilm	AUC	0.9323	0.9364	0.9369	0.9363	0.9354	0.9343	0.9329	0.9313	0.9291	0.9259	0.9183
	SD	0.0028	0.0024	0.0020	0.0018	0.0016	0.0015	0.0015	0.0015	0.0014	0.0014	0.0014