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We discuss the inadequacy of covariances/correlations and other measures inL-2 as relative distance metrics. We propose a computationally simple heuristicto transform a map based on standard principal component analysis (PCA) (whenthe variables are asymptotically Gaussian) into an entropy-based map wheredistances are based on mutual information (MI).

Informational Rescaling of PCA Maps with Application to Genetic Distance