Regularized Generalized Canonical Correlation Analysis: A Framework for Sequential Multiblock Component Methods
Psychometrika - 2017
Tóm tắt
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,
$${\vert }x{\vert }$$
,
$$x^{2}$$
or
$$x^{4}$$
and shrinkage constants 0 or 1, many multiblock component methods are recovered.
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