Chapter 6
Principal Components Analysis
Principal Component
Dimension Reduction
Discovering Structure in The Data
Figure 6.1  A Framework for Multivariate Analysis

Figure 6.1: A Framework for Multivariate Analysis

Principal Component Analysis (PCA) is an exploratory multivariate technique with two overall objectives. One objective is “dimension reduction”— i.e., to turn a collection of, say, 100 variables into a collection of 10 variables that retain almost all the information that was contained in the original 100 variables. The other objective is to discover the structure in the ...

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