Numerical Computing with Python

Singular value decomposition - SVD

Many implementations of PCA use singular value decomposition to calculate eigenvectors and eigenvalues. SVD is given by the following equation:

Columns of U are called left singular vectors of the data matrix, the columns of V are its right singular vectors, and the diagonal entries of are its singular values. Left singular vectors are the eigenvectors of the covariance matrix and the diagonal element of