betweenness.centrality.clustering(RBGL)
betweenness.centrality.clustering()所属R语言包:RBGL
Graph clustering based on edge betweenness centrality
图聚类的基础上边缘中间中心
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Graph clustering based on edge betweenness centrality
图聚类的基础上边缘中间中心
用法----------Usage----------
betweenness.centrality.clustering(g, threshold = -1, normalize = T)
参数----------Arguments----------
参数:g
an instance of the graph class with edgemode “undirected”
graph与edgemode“无向”类的一个实例
参数:threshold
threshold to terminate clustering process
阈值终止聚类过程
参数:normalize
boolean, when TRUE, the edge betweenness centrality is scaled by 2/((n-1)(n-2)) where n is the number of vertices in g; when FALSE, the edge betweenness centrality is the absolute value
布尔值,为TRUE时,边缘中间中心缩放2/((n-1)(n-2))n在g的顶点,为FALSE时,边缘中间中心是绝对值
Details
详情----------Details----------
To implement graph clustering based on edge betweenness centrality.
为了实现基于边缘中间中心的图聚类。
The algorithm is iterative, at each step it computes the edge betweenness centrality and removes the edge with maximum betweenness centrality when it is above the given threshold. When the maximum betweenness centrality falls below the threshold, the algorithm terminates.
是迭代的算法,在每一步计算边缘的中间中心,消除了中间中心最大的边缘时,它上面给定的threshold。当最大的中间中心低于阈值时,算法终止。
See documentation on Clustering algorithms in Boost Graph Library for details.
Boost Graph库中看到有关详细信息,文档聚类算法。
值----------Value----------
A list of
一列
参数:no.of.edges
number of remaining edges after removal
搬迁后的剩余边的数量
参数:edges
remaining edges
剩余的边缘
参数:edge.betweenness.centrality
betweenness centrality of remaining edges
其余边缘的中间中心
作者(S)----------Author(s)----------
Li Long <li.long@isb-sib.ch>
参考文献----------References----------
by Jeremy G. Siek, Lie-Quan Lee, and Andrew Lumsdaine; (Addison-Wesley, Pearson Education Inc., 2002), xxiv+321pp. ISBN 0-201-72914-8
参见----------See Also----------
brandes.betweenness.centrality
brandes.betweenness.centrality
举例----------Examples----------
con <- file(system.file("XML/conn.gxl",package="RBGL"))
coex <- fromGXL(con)
close(con)
coex <- ugraph(coex)
betweenness.centrality.clustering(coex, 0.5, TRUE)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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