A Riemannian Model to Orthonormalized Partial Least Squares

被引：2
|
作者：
Silva, J. W. L. [1 ]
机构：
[1] Univ Estadual Paraiba UEPB, Joao Pessoa, PB, Brazil
来源：
IEEE LATIN AMERICA TRANSACTIONS | 2018年 / 16卷 / 01期
关键词：
Orthonormalized PLS; multivariate analysis; multilinear regression; reduced-rank regression; Riemannian model; generalized Stiefel manifold;
D O I：
10.1109/TLA.2018.8291447
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
One of the most common ways used to ensure the smooth operation of projects in multivariate analysis (MVA) is the use of developed metrics in Euclidean spaces, which are approximations, generally coarse, in non-Euclidean spaces. Metrics in non-Euclidean spaces implies the need to make calculations on curved surfaces studied in differential geometry. In thus paper it is proposed a Riemannian model to orthonormalized partial least squares (OPLS). Results using generalized Stiefel manifold as well a nonlinear search algorithm are developed.
引用
收藏
页码：8 / 12
页数：5
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