gdmp2(g_original: object, min_threshold: float = 0.75) → cdlib.classes.node_clustering.NodeClustering¶
Gdmp2 is a method for identifying a set of dense subgraphs of a given sparse graph. It is inspired by an effective technique designed for a similar problem—matrix blocking, from a different discipline (solving linear systems).
Supported Graph Types
Undirected Directed Weighted Bipartite Yes Yes No Yes Parameters:
- g_original – a networkx/igraph object
- min_threshold – the minimum density threshold parameter to control the density of the output subgraphs, default 0.75
>>> from cdlib import algorithms >>> import networkx as nx >>> G = nx.karate_club_graph() >>> com = algorithms.gdmp2(G)
Chen, Jie, and Yousef Saad. Dense subgraph extraction with application to community detection. IEEE Transactions on Knowledge and Data Engineering 24.7 (2012): 1216-1230.
Reference implementation: https://github.com/imabhishekl/CSC591_Community_Detection