l1spectral (version 0.99.6)

l1spectral-package: Description of the package

Description

l1spectral

Details

l1-spectral clustering is an l1-penalized version of the spectral clustering algorithm, which aims at robustly detecting cluster structure of perturbed graphs by promoting sparse eigenbases solutions of specific l1-minimization problems.

The DESCRIPTION file: l1spectral

References

C. Champion, M. Champion, M. Blaz<U+00E8>re, R. Burcelin, J.M. Loubes, l1-spectral clustering algorithm: a robust spectral clustering using Lasso regularization, Preprint (2021).

See Also

l1_spectralclustering

Examples

# NOT RUN {
 #####################################################
 # Performing the l1-spectral clustering on the graph
 #####################################################

 data(ToyData)

 # if desired, the number of clusters and representative elements can be provided,
 # otherwise remove
 results2 <- l1_spectralclustering(A = ToyData$A_hat, pen = "lasso")
 results2$comm

 # when desired, the number of clusters and representative elements can also be provided
 
# }
# NOT RUN {
results2 <- l1_spectralclustering(A = ToyData$A_hat, pen = "lasso",
              k=2, elements = c(1,4))
# }