ConsensusClust

community detection by concensus (majority voting) initialized by regularized spectral clustering

 community detection 

Model selection and parameter tuning procedures for a class of random network models. The model selection can be done by a general cross-validation framework called ECV from Li et. al. (2016) <arXiv:1612.04717> . Several other model-based and task-specific methods are also included, such as NCV from Chen and Lei (2016) <arXiv:1411.1715>, likelihood ratio method from Wang and Bickel (2015) <arXiv:1502.02069>, spectral methods from Le and Levina (2015) <arXiv:1507.00827>. Many network analysis methods are also implemented, such as the regularized spectral clustering (Amini et. al. 2013 <doi:10.1214/13-AOS1138>) and its degree corrected version and graphon neighborhood smoothing (Zhang et. al. 2015 <arXiv:1509.08588>). It also includes the consensus clustering of Gao et. al. (2014) <arXiv:1410.5837>, the method of moments estimation of nomination SBM of Li et. al. (2020) <arxiv:2008.03652>, and the network mixing method of Li and Le (2021) <arxiv:2106.02803>. It also includes the informative core-periphery data processing method of Miao and Li (2021) <arXiv:2101.06388>. The work to build and improve this package is partially supported by the NSF grants DMS-2015298 and DMS-2015134.

Tianxi Li

randnet

Random Network Model Estimation, Selection and Parameter Tuning

Tianxi Li 

Elizeveta Levina 

Ji Zhu 

Can M. Le 

ConsensusClust function

<dl> <dt>A</dt>
<dd>adjacency matrix</dd> <dt>K</dt>
<dd>number of communities</dd> <dt>tau</dt>
<dd>reguarlization parameter for regularized spectral clustering. Default value is 0.25. Typically set between 0
and 1. If tau=0, no regularization is applied.</dd> <dt>lap</dt>
<dd>indicator. If TRUE, the Laplacian matrix for initializing clustering. If FALSE, the
 adjacency matrix will be used.</dd></dl>

Arguments

Tianxi Li, Elizaveta Levina, Ji Zhu 
Maintainer: Tianxi Li &lt;tianxili@virginia.edu&gt;

Author

clusters nodes by concensus (majority voting) initialized by regularized spectral clustering — ConsensusClust

<dl>

 <dt>A</dt>
<dd>adjacency matrix</dd>

 <dt>K</dt>
<dd>number of communities</dd>

 <dt>tau</dt>
<dd>reguarlization parameter for regularized spectral clustering. Default value is 0.25. Typically set between 0
and 1. If tau=0, no regularization is applied.</dd>

 <dt>lap</dt>
<dd>indicator. If TRUE, the Laplacian matrix for initializing clustering. If FALSE, the
 adjacency matrix will be used.</dd>

</dl>

Tianxi Li, Elizaveta Levina, Ji Zhu 
Maintainer: Tianxi Li &lt;tianxili@virginia.edu&gt;

ConsensusClust: clusters nodes by concensus (majority voting) initialized by regularized spectral clustering

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples