Cluster similarity matrix by graph community detection methods

cluster_by_igraph(mat,
    method = c("cluster_fast_greedy",
    "cluster_leading_eigen",
    "cluster_louvain",
    "cluster_walktrap"),
    ...)

Arguments

mat

The similarity matrix.

method

The community detection method.

...

Other arguments passed to the corresponding community detection function, see Details.

Details

The symmetric similarity matrix can be treated as an adjacency matrix and constructed as a graph/network with the similarity values as the weight of hte edges. Thus, clustering the similarity matrix can be treated as detecting clusters/modules/communities from the graph.

Four methods implemented in igraph package can be used here:

cluster_fast_greedy

uses cluster_fast_greedy.

cluster_leading_eigen

uses cluster_leading_eigen.

cluster_louvain

uses cluster_louvain.

cluster_walktrap

uses cluster_walktrap.

Value

A vector of cluster labels (in numeric).

Examples

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