Multiresolution estimates of classification complexity

In this paper, we study two measures of classification complexity based on feature space partitioning: purity and neighborhood separability. The new measures of complexity are compared with probabilistic distance measures and a number of other nonparametric estimates of classification complexity on a total of 10 databases from the University of California, Irvine, (UCI) repository.