For a more restricted class of classifiers which rely only on any single feature 2 z i , the distance is equal to the maximum over the change in the distributions P (z i ).
for arbitrary linear classifiers we have: It follows that low inter-domain variability of the marginal distributions of latent variables is a necessary condition for low discrepancy distance.