Svd, Singular Values, Eigenvalue, Eigenvectors, Sklearn.
and V_transpose , where U and V_transpose are the same matrix as defined in the SVD theorem but Σ is a one-dimensional array containing the singular values or squares of eigenvalues. Therefore when you multiply these returned matrices, you don’t get back the original matrix and you get errors most