Kernel Generalized Canonical Correlation Analysis - CentraleSupélec
Communication Dans Un Congrès Année : 2010

Kernel Generalized Canonical Correlation Analysis

Arthur Tenenhaus

Résumé

A classical problem in statistics is to study relationships between several blocks of variables. The goal is to find variables of one block directly related to variables of other blocks. The Regularized Generalized Canonical Correlation Analysis (RGCCA) is a very attractive framework to study such a kind of relationships between blocks. However, RGCCA captures linear relations between blocks and to assess nonlinear relations we propose a kernel extension of RGCCA.
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Dates et versions

hal-00553602 , version 1 (07-01-2011)

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  • HAL Id : hal-00553602 , version 1

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Arthur Tenenhaus. Kernel Generalized Canonical Correlation Analysis. JdS'10, May 2010, Marseille, France. CD-ROM Proceedings (6 p.). ⟨hal-00553602⟩
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