robinCompareNoParallel: robinCompareNoParallel

Description

This function compares the robustness of two community detection algorithms.

Usage

robinCompareNoParallel(
  graph,
  method1 = c("walktrap", "edgeBetweenness", "fastGreedy", "leadingEigen", "louvain",
    "spinglass", "labelProp", "infomap", "optimal", "leiden", "other"),
  args1 = list(),
  method2 = c("walktrap", "edgeBetweenness", "fastGreedy", "leadingEigen", "louvain",
    "spinglass", "labelProp", "infomap", "optimal", "leiden", "other"),
  args2 = list(),
  FUN1 = NULL,
  FUN2 = NULL,
  measure = c("vi", "nmi", "split.join", "adjusted.rand"),
  type = c("independent", "dependent"),
  verbose = TRUE
)

Value

A list object with two matrices: - the matrix "Mean1" with the means of the procedure for the first method - the matrix "Mean2" with the means of the procedure for the second method

Arguments

graph: The output of prepGraph.
method1: The first clustering method, one of "walktrap", "edgeBetweenness", "fastGreedy", "louvain", "spinglass", "leadingEigen", "labelProp", "infomap","leiden","optimal","other".
args1: A list of arguments to be passed to the method1 (see i.e. cluster_leiden for a list of possible method parameters).
method2: The second custering method one of "walktrap", "edgeBetweenness","fastGreedy", "louvain", "spinglass", "leadingEigen", "labelProp", "infomap","leiden","optimal","other".
args2: A list of arguments to be passed to the method2 (see i.e. cluster_leiden for a list of possible method parameters).
FUN1: personal designed function when method1 is "other". see methodCommunity.
FUN2: personal designed function when method2 is "other". see methodCommunity.
measure: The stability measure, one of "vi", "nmi", "split.join", "adjusted.rand" all normalized and used as distances. "nmi" refers to 1- nmi and "adjusted.ran" refers to 1-adjusted.rand.
type: The type of robin construction, dependent or independent.
verbose: flag for verbose output (default as TRUE).