Complexity Measures for Classification Problems (ECoL)
Provides measures to characterize the complexity of classification problems based on the ambiguity and the separation between the classes and the data sparsity and dimensionality of the datasets. This package provides bug fixes, generalizations and implementations of many state of the art measures. The measures are described in the paper: Tin Ho and Mitra Basu (2002) <doi:10.1109/34.990132>.

The Essential Histogram (essHist)
Provide an optimal histogram, in the sense of probability density estimation and features detection, by means of multiscale variational inference. For details see Li, Munk, Sieling and Walther (2016) <arXiv:1612.07216>.

Sampler for Verification Studies (valection)
A binding for the ‘valection’ program which offers various ways to sample the outputs of competing algorithms or parameterizations, and fairly assess their performance against each other. The ‘valection’ C library is required to use this package and can be downloaded from: <http://…/valection>. Cooper CI, et al; Valection: Design Optimization for Validation and Verification Studies; Biorxiv 2018; <doi:10.1101/254839>.