SELECT-REGRESS-AND-ROUND : A SIMPLE METHOD FOR CREATING SIMPLE RULES

Funding information N/A Judges, doctors, and managers are among those decision makers who must often choose a course of action under limited time, with limited knowledge, and without the aid of a computer. Because data-drivenmethods typically outperform unaided judgments, resource-constrained practitioners can benefit from simple, statistically derived rules that can be applied mentally. In this work, we formalize longstanding observations about the efficacy of improper linear models to construct accurate yet easily memorized rules. To test the performance of this approach, we conduct a large-scale evaluation in 23 domains and focus in depth on one: judicial decisions to release or detain defendants while they await trial. In these domains, we find that simple rules rival the accuracy of complex predictionmodels that base decisions on considerablymore information. Further, comparing to unaided judicial decisions, we find that simple rules substantially outperform the human experts. To conclude, we present an analytical framework that sheds light onwhy simple rules perform as well as they do.

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