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Interpretable classification models for recidivism prediction


  • Jiaming Zeng
  • Berk Ustun
  • Cynthia Rudin


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Suggested Citation

  • Jiaming Zeng & Berk Ustun & Cynthia Rudin, 2017. "Interpretable classification models for recidivism prediction," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 689-722, June.
  • Handle: RePEc:bla:jorssa:v:180:y:2017:i:3:p:689-722

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    References listed on IDEAS

    1. Richard Berk & Lawrence Sherman & Geoffrey Barnes & Ellen Kurtz & Lindsay Ahlman, 2009. "Forecasting murder within a population of probationers and parolees: a high stakes application of statistical learning," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 191-211.
    2. Hoffman, Peter B., 1994. "Twenty years of operational use of a risk prediction instrument: The United States parole commission's salient factor score," Journal of Criminal Justice, Elsevier, vol. 22(6), pages 477-494.
    3. Friedman, Jerome H., 2002. "Stochastic gradient boosting," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 367-378, February.
    4. N. Tollenaar & P. G. M. van der Heijden, 2013. "Which method predicts recidivism best?: a comparison of statistical, machine learning and data mining predictive models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(2), pages 565-584, February.
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