“Supervised Principal Component Analysis (Supervised PCA)” A generalization of PCA that is uniquely effective for regression and classification problems with high-dimensional input data. It works by estimating a sequence of principal components that have maximal dependence on the response variable.
Keywords: Dimensionality reduction, Principal component analysis (PCA), Kernel methods, Supervised learning, Visualization, Classification, Regression