Data Science, Linear Algebra, Dimensionality Reduction, Math.
multiplier, to maximize variance, the vector “v” has to be the eigenvector of the covariance matrix! This is where the idea of solving eigendecomposition is coming from. That’s why you could solve the PCA without doing some iterative optimization. OK, so at last, what’s the difference between