cdlib.algorithms.em¶
- cdlib.algorithms.em(g_original: object, k: int) NodeClustering ¶
EM is based on based on a mixture model. The algorithm uses the expectation–maximization algorithm to detect structure in networks.
Supported Graph Types
Undirected
Directed
Weighted
Yes
Yes
No
- Parameters:
g_original – a networkx/igraph object
k – the number of desired communities
- Returns:
NodeClustering object
- Example:
>>> from cdlib import algorithms >>> import networkx as nx >>> G = nx.karate_club_graph() >>> com = algorithms.em(G, k=3)
- References:
Newman, Mark EJ, and Elizabeth A. Leicht. Mixture community and exploratory analysis in networks. Proceedings of the National Academy of Sciences 104.23 (2007): 9564-9569.
Note
Reference implementation: https://github.com/duckneo/CommunityDetection