A low-rank constraint could be added, computed for the Lasso-Rank procedure.
A collection of models is constructed, varying the level of sparsity and the
number of clusters, and a model is selected using a model selection criterion
- (slope heuristic, BIC or AIC). Details of the procedure are provided in 'Model-
- based clustering for high-dimensional data. Application to functional data' by
- Emilie Devijver, published in Advances in Data Analysis and Clustering (2016).
+ (slope heuristic, BIC or AIC). Details of the procedure are provided in
+ "Model-based clustering for high-dimensional data. Application to functional data"
+ by Emilie Devijver (2016) <arXiv:1409.1333v2>,
+ published in Advances in Data Analysis and Clustering.
Author: Benjamin Auder <benjamin.auder@universite-paris-saclay.fr> [aut,cre],
Emilie Devijver <Emilie.Devijver@kuleuven.be> [aut],
Benjamin Goehry <Benjamin.Goehry@math.u-psud.fr> [ctb]