Computational Social Networks

Table 11 Riondato2016 clustering results for LFR nets of 10,000 and 100,000 nodes

From: Comparing the speed and accuracy of approaches to betweenness centrality approximation

#	10,000 nodes							100,000 nodes
	\(\mu\)	\(\epsilon =0.2\)		\(\epsilon =0.4\)		\(\epsilon =0.6\)		\(\mu\)	\(\epsilon =0.2\)		\(\epsilon =0.4\)		\(\epsilon =0.6\)
	\(\mu\)	%	s	%	s	%	s	\(\mu\)	%	s	%	s	%	s
1	0.01	100	986	96	331	100	214	0.001	93	2829	71	1520	88	556
2	0.02	84	1649	100	544	100	357	0.003	93	5337	65	2302	88	1045
3	0.03	93	2049	100	625	100	408	0.005	96	6929	69	2851	83	1737
4	0.04	88	2294	100	690	96	427	0.001	96	11,405	97	5452	100	2216
5	0.05	90	2411	94	718	100	447	0.005	96	44,965	96	14,637	100	13,716
6	0.10	82	2845	77	833	88	498	0.010	95	74,826	96	35,526	100	31,403

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