Resampling effects on significance analysis of network clustering and ranking.
Community detection helps us simplify the complex configuration of networks, but communities are reliable only if they are statistically significant. To detect statistically significant communities, a common approach is to resample the original network and analyze the communities. But resampling ass...
Main Authors: | Atieh Mirshahvalad, Olivier H Beauchesne, Eric Archambault, Martin Rosvall |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2013-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC3553110?pdf=render |
Similar Items
-
Significant communities in large sparse networks.
by: Atieh Mirshahvalad, et al.
Published: (2012-01-01) -
Detection of Significant Groups in Hierarchical Clustering by Resampling
by: Paola Sebastiani, et al.
Published: (2016-08-01) -
Organization of information pathways in complex networks
by: Mirshahvalad, Atieh
Published: (2013) -
New resampling method for evaluating stability of clusters
by: Neuhaeuser Markus, et al.
Published: (2008-01-01) -
Resampling Model Selection for Cluster/Longitudinal Data
by: WANG, BO-SIAN, et al.
Published: (2017)