Clusterwise multiblock PLS - Cnam - Conservatoire national des arts et métiers Access content directly
Conference Papers Year : 2018

Clusterwise multiblock PLS

Abstract

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
Fichier principal
Vignette du fichier
SFC_2018_paper_19.pdf (141.85 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02471608 , version 1 (12-09-2021)

Identifiers

  • HAL Id : hal-02471608 , version 1

Cite

Ndèye Niang, Stéphanie Bougeard, Gilbert Saporta. Clusterwise multiblock PLS. SFC 2018, Sep 2018, Paris, France. ⟨hal-02471608⟩
80 View
26 Download

Share

Gmail Facebook X LinkedIn More