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Predicting Recidivism Risk: New Tool in Philadelphia Shows Great Promise

This tool uses random forest modeling to identify probationers likely to reoffend within two years of returning to the community. The tool — which has been successfully used in Philadelphia for four years — assesses each new probation case at its outset and assigns the probationer to a high-, moderate- or low-risk category. Although this is not a new concept, what is unique is that the tool uses “random forest modeling,” a sophisticated statistical approach that considers the nonlinear effects of a large number of variables with complex interactions.


Published: 2013