A Novel Convex Clustering Method for High-Dimensional Data Using Semiproximal ADMM

Table 2

Results for Case II. Empirical mean and standard deviation (SD) of the RI, FMI, FNR, and FPR based on 50 repetitions.

Case II:
	Methods	RI		FMI		FNR		FPR
		Mean	SD	Mean	SD	Mean	SD	Mean	SD
2000	K-means	0.907	0.073	0.848	0.117	0.000	0.000	1.000	0.000
	CC	0.970	0.045	0.942	0.085	0.000	0.000	1.000	0.000
	SCC	0.998	0.002	0.995	0.004	0.000	0.000	0.550	0.127
	SGLCC	0.995	0.021	0.991	0.034	0.015	0.045	0.000	0.000
3000	K-means	0.887	0.087	0.815	0.138	0.000	0.000	1.000	0.000
	CC	0.928	0.029	0.841	0.068	0.000	0.000	1.000	0.000
	SCC	0.997	0.015	0.993	0.032	0.000	0.000	0.681	0.071
	SGLCC	1.000	0.000	1.000	0.000	0.000	0.003	0.000	0.000
4000	K-means	0.892	0.076	0.823	0.122	0.000	0.000	1.000	0.000
	CC	0.925	0.030	0.834	0.069	0.000	0.000	1.000	0.000
	SCC	0.998	0.006	0.996	0.012	0.000	0.000	0.685	0.007
	SGLCC	1.000	0.000	1.000	0.000	0.000	0.001	0.000	0.000
5000	K-means	0.885	0.077	0.810	0.123	0.000	0.000	1.000	0.000
	CC	0.911	0.028	0.800	0.068	0.000	0.000	1.000	0.000
	SCC	0.986	0.033	0.968	0.077	0.000	0.000	0.711	0.085
	SGLCC	1.000	0.000	1.000	0.000	0.000	0.000	0.000	0.000