Machine Learning, Linear Algebra.
from the top k eigenvectors Apply W to D to transform to a k-dimensional feature space where there are less or no redundant data. And there you have it! We have managed to reduce the amount of dimensions from d to k and now our data are much more interpretable and therefore we can build a