What is an intuitive explanation of the relation between PCA and SVD?Answer (1 of 5): Principal Component Analysis (PCA) is a procedure through which we try to remove the redundancy present in the Dataset by projecting the Given Dataset to a different Vector Space such that the Covariance Matrix(of the Dataset in new Space) is Diagonalized. Such a Projection (Tran...
