cdlib.algorithms.endntm¶
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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.