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Foundations
Principal Component Analysis
A classic technique that compresses many correlated variables into a few key dimensions.
Definition
Principal component analysis (PCA) is a classic technique for dimensionality reduction. It finds the directions along which the data varies the most and re-expresses the data using just those few directions, compressing many correlated variables into a handful of informative ones. It is widely used for visualization and noise reduction.