cdlib.algorithms.endntm

endntm(g_original: object, clusterings: list = None, epsilon: float = 2) → cdlib.classes.node_clustering.NodeClustering

Overlapping community detection algorithm based on an ensemble approach with a distributed neighbourhood threshold method (EnDNTM). EnDNTM uses pre-partitioned disjoint communities generated by the ensemble mechanism and then analyzes the neighbourhood distribution of boundary nodes in disjoint communities to detect overlapping communities.

Supported Graph Types

Undirected	Directed	Weighted
Yes	No	No

Parameters:

• g_original – a networkx/igraph object
• clusterings – an iterable of Clustering objects (non overlapping node partitions only)
• epsilon – neighbourhood threshold, default 2.

Returns:

NodeClustering object

Example:

>>> from cdlib import algorithms
>>> import networkx as nx
>>> G = nx.karate_club_graph()
>>> coms_l = [algorithms.louvain(G), algorithms.label_propagation(G), algorithms.walktrap(G)]
>>> coms = algorithms.endntm(G, coms_l)

References:

Jaiswal, R., & Ramanna, S. Detecting overlapping communities using ensemble-based distributed neighbourhood threshold method in social networks. Intelligent Decision Technologies, (2021), doi:10.3233/IDT-200059.