is a dimension-reduction method that 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 using singular value decomposition. Feature Analysis Principal Component Analysis (PCA) Factor Analysis (FA) Linear Discriminant Analysis (LDA) With supervised learning, the primary grouping is: dimension reduction and regression classification and dimension reduction regression and classification exploratory analysis and dimension reduction regression and exploratory analysis