Machine Learning, Dimensionality Reduction, Eigenvectors, Algorithms, Mathematics.
variance of our projected data var(vᵗx). Mathematically, it can be expressed as - var(vᵗx) = E( (vᵗx-E(vᵗx))² ) Skipping over the mathematics, we get variance as follows - var(vᵗx) = vᵗ E(c(x)c(x)ᵗ) v, where c(x) is the mean centered data x-E(x) We can see E(c(x)c(x)ᵗ) is nothing but the Covariance