主成分分析与偏最小二乘回归

Tetrahedron Computer Methodology Pub Date : 1989-01-01 DOI:10.1016/0898-5529(89)90004-3

W.J. Dunn III ∗ , D.R. Scott , W.G. Glen ∗

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引用次数: 124

摘要

从适当的极值条件出发，详细介绍了主成分分析和偏最小二乘回归技术背后的数学。本文还介绍了合成向量的含义及其数学上的相互关系。此外，偏最小二乘被开发为主成分分析的“修改”，以强调这两种技术之间的关系。相邻的论文包括应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Principal components analysis and partial least squares regression

The mathematics behind the techniques of principal component analysis and partial least squares regression is presented in detail, starting from the appropriate extrema conditions. The meaning of the resultant vectors and many of their mathematical interrelationships are also presented. Also, partial least squares is developed as a ‘modification’ of principal component analysis to underline the relationship between these two techniques. The adjacent paper includes applications.

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Tetrahedron Computer Methodology

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