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Predicting criminal recidivism: A comparison of neural network models with statistical methods


  • Caulkins, Jonathan
  • Cohen, Jacqueline
  • Gorr, Wilpen
  • Wei, Jifa


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  • Caulkins, Jonathan & Cohen, Jacqueline & Gorr, Wilpen & Wei, Jifa, 1996. "Predicting criminal recidivism: A comparison of neural network models with statistical methods," Journal of Criminal Justice, Elsevier, vol. 24(3), pages 227-240.
  • Handle: RePEc:eee:jcjust:v:24:y:1996:i:3:p:227-240

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    References listed on IDEAS

    1. Schmidt, Peter & Witte, Ann Dryden, 1989. "Predicting criminal recidivism using 'split population' survival time models," Journal of Econometrics, Elsevier, vol. 40(1), pages 141-159, January.
    2. Greene, Michael A. & Hoffman, Peter B. & Beck, James L., 1994. "The mean cost rating (MCR) is Somers' D: A methodological note," Journal of Criminal Justice, Elsevier, vol. 22(1), pages 63-69.
    3. Kar Yan Tam & Melody Y. Kiang, 1992. "Managerial Applications of Neural Networks: The Case of Bank Failure Predictions," Management Science, INFORMS, vol. 38(7), pages 926-947, July.
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    Cited by:

    1. Palocsay, Susan W. & Wang, Ping & Brookshire, Robert G., 2000. "Predicting criminal recidivism using neural networks," Socio-Economic Planning Sciences, Elsevier, vol. 34(4), pages 271-284, December.
    2. Brendan Cushing-Daniels, 2005. "Even the errors discrimenate: How the split-population model of criminal recidivism makes justice even less colorblind," The Review of Black Political Economy, Springer;National Economic Association, vol. 33(1), pages 25-39, September.

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