BMC Bioinformatics

Table 2 The AUC result for α ∈ [0, 1] with an increment of 0.1

From: Identifying Cancer genes by combining two-rounds RWR based on multiple biological data

	α	0	0.1	0.2	0.3	0.4	0.5	0.6	0.7	0.8	0.9	1
γ	AUC	0	0.1	0.2	0.3	0.4	0.5	0.6	0.7	0.8	0.9	1
0.1		0.8961	0.8996	0.9013	0.9024	0.9027	0.9037	0.9035	0.9036	0.9034	0.9028	0.9032
0.2		0.9004	0.9045	0.9060	0.9070	0.9082	0.9087	0.9088	0.9086	0.9086	0.9084	0.9078
0.3		0.9027	0.9068	0.9086	0.9094	0.9099	0.9104	0.9111	0.9115	0.9112	0.9105	0.9086
0.4		0.9039	0.9082	0.9098	0.9103	0.9110	0.9117	0.9121	0.9128	0.9126	0.9117	0.9083
0.5		0.9047	0.9088	0.9104	0.9111	0.9115	0.9120	0.9125	0.9124	0.9132	0.9127	0.9075
0.6		0.9061	0.91020	0.9118	0.9132	0.9136	0.9148	0.9152	0.9158	0.9170	0.9178	0.9138
0.7		0.9055	0.9098	0.9110	0.9119	0.9125	0.9130	0.9136	0.9140	0.9149	0.9160	0.9109
0.8		0.9054	0.9089	0.9100	0.9112	0.9114	0.9121	0.9126	0.9133	0.9139	0.9148	0.9090
0.9		0.9047	0.9082	0.9090	0.9097	0.9103	0.9110	0.9115	0.9116	0.9126	0.9134	0.9073

δ = 0.5, η_i = 0.25, σ = 0.6, 0.9178 is bold, which represent the best of auc value

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