The principal component analysis (PCA) is a dimension reduction technique used to reduce variables without removing variables.

Question

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PCA reduces the dimensionality of a dataset by transforming the original variables into a new set of variables (principal components) that are linear combinations of the original variables, thus reducing the number of variables without explicitly removing any original variable.

The Principal Component Analysis (PCA) Is a Dimension Reduction Technique