Description Usage Arguments Details Value Author(s) References See Also Examples

Graph clustering based on edge betweenness centrality

1 | ```
betweenness.centrality.clustering(g, threshold = -1, normalize = TRUE)
``` |

`g` |
an instance of the |

`threshold` |
threshold to terminate clustering process |

`normalize` |
boolean, when TRUE, the edge betweenness centrality is
scaled by |

To implement graph clustering based on edge betweenness centrality.

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.

See documentation on Clustering algorithms in Boost Graph Library for details.

A list of

`no.of.edges` |
number of remaining edges after removal |

`edges` |
remaining edges |

`edge.betweenness.centrality` |
betweenness centrality of remaining edges |

Li Long <[email protected]>

Boost Graph Library ( www.boost.org/libs/graph/doc/index.html )

The Boost Graph Library: User Guide and Reference Manual; by Jeremy G. Siek, Lie-Quan Lee, and Andrew Lumsdaine; (Addison-Wesley, Pearson Education Inc., 2002), xxiv+321pp. ISBN 0-201-72914-8

`brandes.betweenness.centrality`

1 2 3 4 5 | ```
con <- file(system.file("XML/conn.gxl",package="RBGL"))
coex <- fromGXL(con)
close(con)
coex <- ugraph(coex)
betweenness.centrality.clustering(coex, 0.5, TRUE)
``` |

```
Loading required package: graph
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
rbind, rownames, sapply, setdiff, sort, table, tapply, union,
unique, unsplit, which, which.max, which.min
$no.of.edges
[1] 14
$edges
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
from "A" "A" "A" "B" "B" "C" "D" "D" "E" "E" "E" "H" "H" "F"
to "B" "C" "D" "C" "D" "D" "E" "H" "G" "H" "F" "F" "G" "G"
$edge.betweenness.centrality
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
centrality 1 1 5 1 5 5 8 8 3 1 3 3 3
[,14]
centrality 1
```

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.