Data Mining - Principal Component (Analysis|Regression ...
Principal Component Analysis (PCA) is a feature extraction method that use orthogonal linear projections to capture the underlying variance of the data. By far, the most famous dimension reduction approach is principal component regression. (PCR). PCA can be viewed as a special scoring method under the SVD algorithm.It produces projections that are scaled with the data variance.