A Branch-and-bound Algorithm for Boolean Regression

This paper proposes a branch-and-bound algorithm to trace disjunctive (conjunctive) combinations of binary predictor variables to predict a binary criterion variable. The algorithm allows for finding logical classification rules that can be used to derive whether or not a given object belongs to a given category based on the attribute pattern of the object. An objective function is minimized which takes into account both accuracy in prediction and cost of the predictors. A simulation study is presented in which the performance of the algorithm is evaluated.