cdlib.algorithms.frc_fgsn¶
- cdlib.algorithms.frc_fgsn(g_original: object, theta: float, eps: float, r: int) 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.
Note
Reference implementation: https://github.com/nidhisridhar/Fuzzy-Community-Detection