statistical sampling minimax sampling Alejandra Gonzalez-Beltran In imbalanced datasets, where the sampling ratio does not follow the population statistics, one can resample the dataset in a conservative manner called minimax sampling. The minimax sampling has its origin in Anderson minimax ratio whose value is proved to be 0.5: in a binary classification, the class-sample sizes should be chosen equally. This ratio can be proved to be minimax ratio only under the assumption of LDA classifier with Gaussian distributions. The notion of minimax sampling is recently developed for a general class of classification rules, called class-wise smart classifiers. Philippe Rocca-Serra https://en.wikipedia.org/wiki/Sampling_(statistics)#Minimax_sampling ready for release