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Clusterwise multiblock PLS

Ndèye Niang 1 Stéphanie Bougeard 2 Gilbert Saporta 1
1 CEDRIC - MSDMA - CEDRIC. Méthodes statistiques de data-mining et apprentissage
CEDRIC - Centre d'études et de recherche en informatique et communications
2 ANSES - Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail
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
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Conference papers
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https://hal-cnam.archives-ouvertes.fr/hal-02471608
Contributor : Ndeye Niang Connect in order to contact the contributor
Submitted on : Sunday, September 12, 2021 - 2:12:38 PM
Last modification on : Friday, October 8, 2021 - 4:06:07 PM

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  • HAL Id : hal-02471608, version 1

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CNAM | CEDRIC-CNAM | ANSES | UNIV-HESAM

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

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