cdlib.evaluation.variation_of_information

variation_of_information(first_partition: object, second_partition: object) → cdlib.evaluation.comparison.MatchingResult

Variation of Information among two nodes partitions.

$$ H(p)+H(q)-2MI(p, q) $$

where MI is the mutual information, H the partition entropy and p,q are the algorithms sets

Parameters:
  • first_partition – NodeClustering object
  • second_partition – NodeClustering object
Returns:

MatchingResult object
Example: 
>>> from cdlib import evaluation, algorithms
>>> g = nx.karate_club_graph()
>>> louvain_communities = algorithms.louvain(g)
>>> leiden_communities = algorithms.leiden(g)
>>> evaluation.variation_of_information(louvain_communities,leiden_communities)
Reference:
  1. Meila, M. (2007). Comparing clusterings - an information based distance. Journal of Multivariate Analysis, 98, 873-895. doi:10.1016/j.jmva.2006.11.013