Dimensionality Reduction, Svd, Singular Values, Matrix Factorization, Eigenvectors.
important the component is and the more variance they describe. Step 4 Now that we have our V and Sigma matrices, now it’s time to find U. We can just multiply the equation by sigma(inverse) and V on both sides to get the equation for U. In this case, as V is an orthogonal matrix, the transpose and