Graph Scoring Functions"

In clustAnalytics: Cluster Evaluation on Graphs

knitr::opts_chunk$set(
  collapse = TRUE,
  warning = FALSE,
  comment = "#>"
)

library(clustAnalytics)

The package includes efficient implementations of the clustering coefficient and transitivity for weighted networks introduced by \cite{clustcoeficient}. As they can be applied to weighted graphs in general and not only to their partition into communities, they are simply called with the graph as the only argument:

data(karate, package="igraphdata")
weighted_clustering_coefficient(karate)

To be able to obtain the result for every community in the graph, we provide the function apply_subgraphs; which given a graph, a membership vector and a scalar function, applies the function to every community and returns the vector of results. In this case it works as follows:

apply_subgraphs(karate, V(karate)$Faction, weighted_clustering_coefficient)

clustAnalytics documentation built on May 29, 2024, 12:18 p.m.