This paper addresses the 0-1 outcome feature selection problem. In such a problem, a set of features leads to an outcome that is 0 or 1, depending upon the values of the features. The goal is to extract subsets of features that characterize at best outcome 1. This kind of problem arises in medical analysis, quality control and, generally, in any domain that requires series of expensive tests to evaluate the state of a system.