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Greedy optimization method attempts to optimize the "modularity" of a partition of the network.
Several optimization methods attempt to optimize the " modularity" of a partition of the network [30].
This method is based on a greedy algorithm that attempts to optimize the modularity of a partition of a given network.
In this work, we improve the algorithm of Newman [ 18] to optimize the modularity score.
To determine communities in the graph, a fast-greedy algorithm was used to optimize the modularity of a partition of the network [ 57].
We can adopt the corresponding spectral algorithms and use the leading k eigenvectors of 2 A − B to optimize the modularity density D. To obtain the final network partition, we apply the k-means clustering method to cluster eigenvectors.
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Louvain optimizes the modularity measure of a graph using a greedy search paradigm.
Given a graph G, MODUA finds communities by optimizing the modularity score locally and it terminates until a maximal modularity score is obtained.
Finally, we optimized the modularity in each cellular compartment individually (Additional file 1, Figure S3).
Then the topological structure revealed by optimizing the modularity for A r is that of large groups for small values of r, and smaller groups for large values of r, all of which are strictly embedded in the original topology.
Our algorithm optimizes the likelihood modularity, which is asymptotically consistent (Bickel and Chen, 2009).
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