Principal Component Analysis (PCA) in R

Performing principle component analysis and principle component in R. Principal component analysis (PCA) is a technique for reducing the dimensionality of such datasets, increasing interpretability but at the same time minimizing information loss. It does so by creating new uncorrelated variables that successively maximize variance.