BMC Medical Genomics

Table 1 The average NMIs/ACCs and the standard errors obtained by the ECMC and other comparison partners in seven simulation data sets

From: Subtype identification from heterogeneous TCGA datasets on a genomic scale by multi-view clustering with enhanced consensus

	Methods	Simulation 1				Simulation 2
		t = 0.95	t = 1	t = 1.2	t =2	s = 25	s= 30	s =40	s = 50
NMI	SV1	0.856	0.465	0.007	0.006	0.524	0.470	0.404	0.337
	SV2	0.775	0.495	0.012	0.002	0.524	0.470	0.421	0.331
	Concat	0.919	0.696	0.021	0.006	0.527	0.472	0.421	0.340
	Coreg	0.919	0.566	0.344	0.007	0.542	0.491	0.421	0.344
	SNF	0.960	0.889	0.012	0.005	0.562	0.510	0.421	0.519
	CMC	0.919	0.542	0.493	0.335	0.594	0.503	0.480	0.744
	ECMC	1.000	0.882	1.000	1.000	0.667	1.000	0.859	1.000
ACC	SV1	0.975	0.878	0.550	0.545	0.875	0.850	0.800	0.745
	SV2	0.960	0.886	0.565	0.525	0.875	0.850	0.800	0.750
	Concat	0.990	0.945	0.585	0.545	0.875	0.850	0.800	0.748
	Coreg	0.990	0.910	0.770	0.550	0.875	0.850	0.800	0.750
	SNF	0.995	0.985	0.565	0.540	0.875	0.850	0.800	0.780
	CMC	0.990	0.890	0.777	0.701	0.875	0.850	0.800	0.890
	ECMC	1.000	0.975	1.000	1.000	0.898	1.000	0.980	1.000

Highest NMIs/ACCs are marked in bold

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