Principal Component Analysis (PCA) is a technique used to emphasise variation and bring out strong patterns in a dataset that is a dimension-reduction tool, and can be used to reduce a large set of variables to a small set that still contains most of the information in the large set. A PCA used to make data easy to explore and visualize, and was invented in 1901 by Karl PearsonIt’s.
Related Definitions in the Project: The Project Management
