How to explain Principal Component Analysis and Factor Analysis in a simple and understandable sentence?
Principal Component Analysis (PCA) is a dimensionality reduction technique that identifies and summarizes the primary patterns of variation in the data, whereas Factor Analysis (FA) aims to uncover latent, unobservable variables that are presumed to underlie and influence the observed measurements.
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