inferCommunitiesGreedily: Community detection, greedy algorithm
In sverchkov/CommunityInference: Community Inference for Weighted Graphs
Description
Usage
Arguments
Value
Author(s)
Description
A naive implementation of community detection in a fully-connected weighted graph based on
Newman ME, Girvan M. Finding and evaluating community structure in networks.
Physical review E. 2004 Feb 26;69(2):026113.
Usage
1
2
inferCommunitiesGreedily(similarities, save.file = NULL,
full_trajectory = F, simplify = T, loop_limit = Inf)
Arguments
similarities
a data frame with columns a, b, similarity representing the similarities between nodes.
We assume undirected graph and b < a.
Value
a data frame with two columns, n - node id (taken from a, b of input) and cluster - unique cluster ID.
Author(s)
Yuriy Sverchkov
sverchkov/CommunityInference documentation built on May 7, 2019, 7:42 a.m.
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Description Usage Arguments Value Author(s)
Description
A naive implementation of community detection in a fully-connected weighted graph based on Newman ME, Girvan M. Finding and evaluating community structure in networks. Physical review E. 2004 Feb 26;69(2):026113.
Usage
1 2 | inferCommunitiesGreedily(similarities, save.file = NULL,
full_trajectory = F, simplify = T, loop_limit = Inf)
|
Arguments
similarities |
a data frame with columns a, b, similarity representing the similarities between nodes. We assume undirected graph and b < a. |
Value
a data frame with two columns, n - node id (taken from a, b of input) and cluster - unique cluster ID.
Author(s)
Yuriy Sverchkov
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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