cdlib.evaluation.normalized_mutual_information

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

Normalized Mutual Information between two clusterings.

Normalized Mutual Information (NMI) is an normalization of the Mutual Information (MI) score to scale the results between 0 (no mutual information) and 1 (perfect correlation). In this function, mutual information is normalized by sqrt(H(labels_true) * H(labels_pred))

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.normalized_mutual_information(louvain_communities,leiden_communities)