“Great in, great out” is the new “garbage in, garbage out”: subsampling from data with no response variable using various approaches, including unsupervised learning

When having more initial data than needed, an appropriate selection of a subpopulation from the given dataset, i. e. subsampling, follows, usually intending to ensure all categorical variables’ levels are nearly equally covered and all numerical variables are all well balanced. If a response variable in the original data is missing, popular propensity scoring cannot be performed.This study address...