Principal Components Used with Other Multivariate Techniques
Principal component analysis is often used as a dimension-reducing technique within some other type of analysis. For example, Chapter 8 described the use of PCs as regressor variables in a multiple regression analysis. The present chapter discusses three multivariate techniques, namely discriminant analysis, cluster analysis and canonical correlation analysis; for each of these three techniques, examples are given in the literature which use PCA as a dimension-reducing technique.
KeywordsCluster Analysis Discriminant Analysis Linear Discriminant Analysis Mahalanobis Distance Canonical Correlation Analysis
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