cdlib.algorithms.frc_fgsn

frc_fgsn(g_original: object, theta: float, eps: float, r: int) → cdlib.classes.fuzzy_node_clustering.FuzzyNodeClustering

Fuzzy-Rough Community Detection on Fuzzy Granular model of Social Network.

FRC-FGSN assigns nodes to communities specifying the probability of each association. The flattened partition ensure that each node is associated to the community that maximize such association probability. FRC-FGSN may generate orphan nodes (i.e., nodes not assigned to any community).

Supported Graph Types

Undirected Directed Weighted BiPartite
Yes No No Yes
Parameters:
  • g_original – networkx/igraph object
  • theta – community density coefficient
  • eps – coupling coefficient of the community. Ranges in [0, 1], small values ensure that only strongly connected node granules are merged togheter.
  • r – radius of the granule (int)
Returns:

FuzzyNodeClustering object

Example:
>>> from cdlib import algorithms
>>> import networkx as nx
>>> G = nx.karate_club_graph()
>>> coms = frc_fgsn(G, theta=1, eps=0.5, r=3)
References:

Kundu, S., & Pal, S. K. (2015). Fuzzy-rough community in social networks. Pattern Recognition Letters, 67, 145-152.