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Community Detection in Graphs

Orange.network.community.label_propagation(G, results2items=0, resultHistory2items=0, iterations=1000, seed=None)

Label propagation for community detection, Raghavan et al., 2007

Parameters:
  • G (Orange.network.Graph) – A Orange graph.
  • results2items (bool) – Append a new feature result to items (Orange.data.Table).
  • resultHistory2items (bool) – Append new features result to items (Orange.data.Table) after each iteration of the algorithm.
  • iterations (int) – The maximum number of iterations if there is no convergence.
Orange.network.community.label_propagation_hop_attenuation(G, results2items=0, resultHistory2items=0, iterations=1000, delta=0.1, node_degree_preference=0)

Label propagation for community detection, Leung et al., 2009

Parameters:
  • G (Orange.network.Graph) – A Orange graph.
  • results2items (bool) – Append a new feature result to items (Orange.data.Table).
  • resultHistory2items (bool) – Append new features result to items (Orange.data.Table) after each iteration of the algorithm.
  • iterations (int) – The max. number of iterations if no convergence.
  • delta (float) – The hop attenuation factor.
  • node_degree_preference (float) – The power on node degree factor.