cdlib.evaluation.overlapping_normalized_mutual_information_MGH¶
- cdlib.evaluation.overlapping_normalized_mutual_information_MGH(first_partition: object, second_partition: object, normalization: str = 'max') MatchingResult ¶
Overlapping Normalized Mutual Information between two clusterings.
Extension of the Normalized Mutual Information (NMI) score to cope with overlapping partitions. This is the version proposed by McDaid et al. using a different normalization than the original LFR one. See ref. for more details.
- Parameters:
first_partition – NodeClustering object
second_partition – NodeClustering object
normalization – one of “max” or “LFK”. Default “max” (corresponds to the main method described in the article)
- Returns:
MatchingResult object
- Example:
>>> from cdlib import evaluation, algorithms >>> import networkx as nx >>> g = nx.karate_club_graph() >>> louvain_communities = algorithms.louvain(g) >>> leiden_communities = algorithms.leiden(g) >>> evaluation.overlapping_normalized_mutual_information_MGH(louvain_communities,leiden_communities) :Reference:
McDaid, A. F., Greene, D., & Hurley, N. (2011). Normalized mutual information to evaluate overlapping community finding algorithms. arXiv preprint arXiv:1110.2515. Chicago