Regularized generalized canonical correlation analysis for multiblock or multigroup data analysis

Abstract : This paper presents an overview of methods for the analysis of data structured in blocks of variables or in groups of individuals. More specifically, regularized generalized canonical correlation analysis (RGCCA), which is a unifying approach for multiblock data analysis, is extended to be also a unifying tool for multigroup data analysis. The versatility and usefulness of our approach is illustrated on two real datasets.
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Article dans une revue
European Journal of Operational Research, Elsevier, 2014, 238 (2), pp.391-403
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https://hal-supelec.archives-ouvertes.fr/hal-01071421
Contributeur : Alexandra Siebert <>
Soumis le : mardi 14 octobre 2014 - 11:32:05
Dernière modification le : lundi 16 avril 2018 - 16:59:02

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  • HAL Id : hal-01071421, version 1

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Arthur Tenenhaus, Michel Tenenhaus. Regularized generalized canonical correlation analysis for multiblock or multigroup data analysis. European Journal of Operational Research, Elsevier, 2014, 238 (2), pp.391-403. 〈hal-01071421〉

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