Applied Network Science

Table 3 Optimal Cluster configuration by graph type and resilience measures

From: Applications of node-based resilience graph theoretic framework to clustering autism spectrum disorders phenotypes

	Complete clustering				No node reassignment
	Integrity k=3	Tenacity k=5	VAT k=4	kNN3 Integrity ^ak=5	VAT k=2	Integrity k=5	Tenacity k=5
Silhouette ↑	0.11	0.05	0.07	0.07	0.12	0.04	0.05
Davies-Bouldin ↓	3.18	4.28	4.19	4.40	3.37	3.66	3.75
Xie-Beni ↓	3.38	7.16	8.10	8.92	3.01	5.77	6.48
Dunn ↑	0.13	0.15	0.15	0.17	0.14	0.14	0.14
Calinski-Harabasz ↑	152.57	154.11	166.22	165.32	167.71	142.52	141.58
I Index ↑	0.14	0.08	0.12	0.08	0.12	0.06	0.09
SD Index ↓	9.96	14.62	14.40	20.10	8.52	7.71	9.10
SDb w Index ↓	1.37	1.07	1.16	1.06	1.87	1.10	1.05
CVNN Index ↓	1.38	0.95	1.21	0.54	2.00	2.00	2.00
Separability ↑	31.63	11.14	20.21	8.34	8.53	11.39	15.25
Modularity (> 0.6)	0.42	0.72	0.65	0.68	0.27	0.67	0.68
Conductance (< 0.07)	0.02	0.04	0.03	0.06	0.06	0.05	0.04

^akNN3 using Integrity measure on correlation filtered data

Back to article page