1. Multiway generalized canonical correlation analysis
- Author
-
Ghislaine Dehaene-Lambertz, Arthur Tenenhaus, Vincent Frouin, Laurent Le Brusquet, Giulia Gennari, Cathy Philippe, Arnaud Gloaguen, Laboratoire des signaux et systèmes (L2S), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Service NEUROSPIN (NEUROSPIN), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Centre National de la Recherche Scientifique (CNRS), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Statistics and Probability ,Multivariate analysis ,Computation ,Structure (category theory) ,01 natural sciences ,[SCCO]Cognitive science ,010104 statistics & probability ,[STAT.ML]Statistics [stat]/Machine Learning [stat.ML] ,0504 sociology ,[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] ,Tensor (intrinsic definition) ,Partial least squares regression ,Convergence (routing) ,Humans ,Applied mathematics ,Computer Simulation ,Least-Squares Analysis ,[MATH]Mathematics [math] ,0101 mathematics ,ComputingMilieux_MISCELLANEOUS ,Mathematics ,[STAT.AP]Statistics [stat]/Applications [stat.AP] ,05 social sciences ,050401 social sciences methods ,Electroencephalography ,General Medicine ,Canonical Correlation Analysis ,Generalized canonical correlation ,Principal component analysis ,Statistics, Probability and Uncertainty ,[STAT.ME]Statistics [stat]/Methodology [stat.ME] ,Algorithms - Abstract
Summary Regularized generalized canonical correlation analysis (RGCCA) is a general multiblock data analysis framework that encompasses several important multivariate analysis methods such as principal component analysis, partial least squares regression, and several versions of generalized canonical correlation analysis. In this article, we extend RGCCA to the case where at least one block has a tensor structure. This method is called multiway generalized canonical correlation analysis (MGCCA). Convergence properties of the MGCCA algorithm are studied, and computation of higher-level components are discussed. The usefulness of MGCCA is shown on simulation and on the analysis of a cognitive study in human infants using electroencephalography (EEG).
- Published
- 2020
- Full Text
- View/download PDF