Table 2.

Simulation results for Models 5–8. (n, p, s) = (200, 1100, 44). Sensitivity, specificity, MCC, number of selected genes, number of false positives (FPs), and mean squared error (MSE) were averaged over 50 replicates. Lnet: Laplcian net; AdaLnet: adaptive Laplacian net; Lasso: ℓ₁-penalty; Enet: elastic net; GL_γ: group ℓ_γ-penalty. Standard errors are given in the Supplementary Material.

Method	Sensitivity	Specificity	MCC	# of genes	# of FPs	MSE
Model 5
Lnet	0.491	0.989	0.575	10.65	12.08	0.077
AdaLnet	0.567	0.996	0.687	29.55	4.62	0.077
Lasso	0.339	0.977	0.337	39.61	24.71	0.073
Enet	0.649	0.985	0.651	44.83	16.28	0.078
GLγ	0.377	0.999	0.586	17.46	0.88	0.076
Model 6
Lnet	0.439	0.996	0.600	23.52	4.22	0.076
AdaLnet	0.642	0.996	0.732	31.43	3.98	0.076
Lasso	0.404	0.973	0.369	46.74	28.98	0.069
Enet	0.650	0.988	0.675	41.61	13.00	0.078
GLγ	0.523	0.998	0.686	24.78	1.75	0.076
Model 7
Lnet	0.518	0.985	0.553	35.06	16.43	0.067
AdaLnet	0.587	0.992	0.639	29.61	8.48	0.067
Lasso	0.424	0.969	0.349	47.99	32.73	0.061
Enet	0.656	0.983	0.610	42.05	18.42	0.069
GLγ	0.507	0.994	0.606	24.87	6.62	0.066
Model 8
Lnet	0.483	0.993	0.582	24.83	7.45	0.067
AdaLnet	0.641	0.992	0.673	31.84	8.76	0.067
Lasso	0.458	0.969	0.373	49.22	32.74	0.059
Enet	0.676	0.984	0.632	41.10	16.78	0.069
GLγ	0.564	0.994	0.647	26.41	6.10	0.067