Difference between revisions of "Louvain Clustering"

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# start with each node being a singleton cluster:
 
# start with each node being a singleton cluster:
 
# consider nodes in random order
 
# consider nodes in random order
# repeat as long as cluster membership changes, consider nodes in a random order
+
# repeat as long as cluster membership changes
 
#* for each node : remove it from its current cluster and add it to the cluster with the highest modularity gain
 
#* for each node : remove it from its current cluster and add it to the cluster with the highest modularity gain
 
# aggregate the resulting clustering to a new graph and continue with step 1 (as long as modularity improves).
 
# aggregate the resulting clustering to a new graph and continue with step 1 (as long as modularity improves).

Revision as of 14:42, 2 April 2015

Louvain Clustering

Method

The Louvain clustering tries to optimize modularity in a greedy fashion by randomly moving nodes from one cluster to another in multiple levels.

The algorithm is:

  1. start with each node being a singleton cluster:
  2. consider nodes in random order
  3. repeat as long as cluster membership changes
    • for each node : remove it from its current cluster and add it to the cluster with the highest modularity gain
  4. aggregate the resulting clustering to a new graph and continue with step 1 (as long as modularity improves).


Complexity

Practically, the algorithm seems to scale well for large graphs.

References