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The great methods bake-off: Comparing performance of machine learning algorithms

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  • Kigerl, Alex
  • Hamilton, Zachary
  • Kowalski, Melissa
  • Mei, Xiaohan

Abstract

Risk assessments have been constructed using a variety of algorithms, from bivariate associations, to regression, to advanced machine learning (ML) approaches. While promising greater accuracy, agencies are hesitant to adopt tools using newer ML approaches, noting concerns of bias and transparency. Research is needed to identify optimal scenarios for algorithm use in assessment development.

Suggested Citation

  • Kigerl, Alex & Hamilton, Zachary & Kowalski, Melissa & Mei, Xiaohan, 2022. "The great methods bake-off: Comparing performance of machine learning algorithms," Journal of Criminal Justice, Elsevier, vol. 82(C).
    • Handle: RePEc:eee:jcjust:v:82:y:2022:i:c:s0047235222000666
    DOI: 10.1016/j.jcrimjus.2022.101946
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    References listed on IDEAS

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