betweenness.centrality.clustering {RBGL} | R Documentation |
Graph clustering based on edge betweenness centrality
betweenness.centrality.clustering(g, threshold = -1, normalize = T))
g |
an instance of the graph class with edgemode
“undirected” |
threshold |
threshold to terminate clustering process |
normalize |
boolean, when true, the threshold is compared with the normalized edge centrality based on the input graph; when false, the threshold is compared with the absolute edge centrality |
This algorithm implements graph clustering based on edge betweenness centrality. It is an iterative algorithm, where in each step it compute the edge betweenness centrality and removes the edge with the maximum betweenness centrality.
edges |
|
betweenness.centrality.clustering |
Li Long <li.long@isb-sib.ch>
Boost Graph Library by Siek et al.
coex <- fromGXL(file(system.file("XML/conn.gxl",package="RBGL"))) coex@edgemode <- "undirected" betweenness.centrality.clustering(coex)