cdlib.evaluation.jaccard_index

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

This function calculates the Jaccard index between two clusterings.

\[J = \frac{N11}{(N11+N10+N01)}\]

Parameters:

• first_partition – NodeClustering object

• second_partition – NodeClustering object

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.jaccard_index(louvain_communities,leiden_communities)

Reference:

Paul Jaccard. The distribution of the flora in the alpine zone. New Phytologist, 11(2):37–50, 1912.

Note

The function requires the clusim library to be installed. You can install it via pip: pip install clusim