Starting with a data set of population P, containing N physicochemical candidate descriptive parameters (ϕ i ) and a target quantity of interest Y , e.g. a material's property, SGD searches along the ϕ i -space and identifies subsets of data or subgroups (SGs) with outstanding distributions of Y . These SGs are identified by selectors (σ i ) or "rules" which can be used to obtain physical insights and to screen for new materials outside the training data set. The rules typically have the form: