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[NBS18] Clusterwise multiblock PLS
Conférence Nationale avec comité de lecture : SFC 2018, September 2018, PARIS, FRANCE,Mots clés: Multiblock component method. Clusterwise regression. Cluster analysis. Dimension reduction
Résumé:
Clusterwise linear regression aims at partitioning a dataset into clusters
characterized by their own regression coefficients. To deal with multiblock
data, an extension of clusterwise regression to multiblock PLS is proposed. As
this method is component-based, it may handle high dimensional data. The interest
of the proposed method will be illustrated on the basis of a simulation
study
Collaboration:
ANSES
BibTeX
| @inproceedings { | |||
| NBS18, | |||
| title | = | "{Clusterwise multiblock PLS }", | |
| author | = | " N. Niang Keita and S. Bougeard and G. Saporta ", | |
| booktitle | = | "{SFC 2018}", | |
| year | = | 2018, | |
| month | = | "September", | |
| address | = | "PARIS, FRANCE", | |
| } | |||
