Abstract: Characterizing subpopulations by their response to a given exposure relative to an alternative. Data for a set of subjects is received, including two exposures, two outcomes, and a set of characteristics. For a number of subsets an outcome model that estimates the probability of an outcome, given an exposure and the characteristics, is trained; an individual odds ratio (iOR), based on the outcome model, is computed; a sparse model that classifies subjects into a high-iOR group or another group is trained; the characteristics used in the sparse model are recorded; and, based on the recorded characteristics, a primary set of characteristics is selected. Another outcome model, based on the set of subjects and the characteristics, is trained. An iOR based on the other outcome model is computed. A sparse model for classifying subjects into a high-iOR group or another group, using the primary set of characteristics, is trained.