Regularized Generalized Canonical Correlation Analysis: A Framework for Sequential Multiblock Component Methods View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-09

AUTHORS

Michel Tenenhaus, Arthur Tenenhaus, Patrick J. F. Groenen

ABSTRACT

A new framework for sequential multiblock component methods is presented. This framework relies on a new version of regularized generalized canonical correlation analysis (RGCCA) where various scheme functions and shrinkage constants are considered. Two types of between block connections are considered: blocks are either fully connected or connected to the superblock (concatenation of all blocks). The proposed iterative algorithm is monotone convergent and guarantees obtaining at convergence a stationary point of RGCCA. In some cases, the solution of RGCCA is the first eigenvalue/eigenvector of a certain matrix. For the scheme functions x, [Formula: see text], [Formula: see text] or [Formula: see text] and shrinkage constants 0 or 1, many multiblock component methods are recovered. More... »

PAGES

737-777

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11336-017-9573-x

DOI

http://dx.doi.org/10.1007/s11336-017-9573-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1085570622

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28536930


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