What is a good metric for assessing the quality of a pcaprincipal component analysis (PCA)?
I performed this algorithm on a dataset. My objective was to reduce the number of features (the information was very redundant). I know the percentage of variance kept is a good indicator of how much information we keep, be are there other information metrics I can use to make sure I removed redundant information and didn't 'lose' such information?