Implemented (not tested) the corrected classifier based on minimal/average canonical angle as a measure of similarity between subspaces. Still have to pad eigenvector matrices with 0, which isn't too good - as the graph do not have the same number of vertices, their eigenvectors are not really lying on a common high-dimensional space. It might be worth it to enforce a fixed number of vertices for this reason.