ABSTRACT

In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data. How can regression analysis and PCA be combined in a beneficial way? Why and when is it a good idea to combine them? Wha

chapter 1|20 pages

Introduction

chapter 2|50 pages

Mathematical Foundation

chapter 4|62 pages

Special Cases and Related Methods

chapter 5|22 pages

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