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

Alex Kigerl, Zachary Hamilton, Melissa Kowalski and Xiaohan Mei

Journal of Criminal Justice, 2022, vol. 82, issue C

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.

Keywords: Risk assessment; Machine learning; Prediction; Algorithm (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jcjust:v:82:y:2022:i:c:s0047235222000666

DOI: 10.1016/j.jcrimjus.2022.101946

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