Eigenvectors, Eigenvalue, Data Science, Machine Learning, Principal Component.
or the “new” features. The process of PCA is just calculating the feature covariance matrix and applying eigendecomposition to get these new and improved features. Their associated eigenvalues describe just how important each new feature is in describing the underlying structure of the data; so