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Is there a way to calculate the explained variance (eigenvalues) from scikit learn's MDS? I've seen this thread, but I think scikit learn's MDS is a "non-classical" form of MDS, so I'm guessing it wouldn't work? Is there a way to compute the explained variance from running scikit learn's implementation of MDS?

Also, if I'm using a precomputed dissimilarity matrix for scikit learn's MDS, is it then running classical MDS? Based on the code it seems like it's still running the SMACOF algorithm regardless (rather than eigendecomposition)?

thestatnoob
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