Dimensionality Reduction, Eigenvectors, Eigenvalue, Data Science, Machine Learning.
so-called principal components). The Eigenvalue in our scenario, gives the loss since reducing dimensions results in loss of information. Thus, the Eigenvector of the largest Eigenvalue is the most important and should be kept, if you want to minimize ‘loss’. The proof of this is quite elegant,