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The great methods bake-off

Comparing performance of machine learning algorithms

Bibliographic Data

ID10913098
AuthorsAlex Kigerl (0000-0002-0556-7423, University of Nebraska at Omaha), Zachary Hamilton (0000-0003-2587-0865, University of Nebraska at Omaha, corresponding author), Melissa A Kowalski (0000-0002-8289-2932), Melissa Kowalski, Xiaohan Mei (0000-0002-7424-8178, California State University Los Angeles)
Year2022
Volume82
Pages101946
Publication date2022-09-01
Open AccessYes
TypeARTICLE
VenueJournal of Criminal Justice (JOURNAL)
Journal identifiersISSN: 0047-2352 • E-ISSN: 1873-6203
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.jcrimjus.2022.101946
OpenAlexW4281619588
LanguageEN
Citations received1
References cited47

Algorithm · Artificial neural network · Data mining · Logistic regression · Machine learning · Random forest · Sample (material · Sample size determination · Statistics · Support vector machine · Transparency (behavior · Adversarial Robustness in Machine Learning · Artificial Intelligence · Computer Science · Crime Patterns and Interventions · Explainable Artificial Intelligence (XAI · Mathematics

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  • The Psychology of Criminal Conduct

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  • The Elements of Statistical Learning

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  • The Recent Past and Near Future of Risk and/or Need Assessment

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  • To Explain or to Predict?

    Galit Shmueli•Statistical Science•2010

  • Comparing effect sizes in follow-up studies

    Marnie E Rice, Grant T Harris•Law and Human Behavior•2005

  • Thirty years of research on the Level of Service Scales

    Mark E Olver, Keira C Stockdale et al.•Psychological Assessment•2014

  • Women’s Risk Factors and Their Contributions to Existing Risk/Needs Assessment

    Open Access•PATRICIA VAN VOORHIS, Emily M Wright et al.•Criminal Justice and Behavior•2010

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    Open Access•Jerome Friedman, Jerome H Friedman et al.•Journal of Statistical Software•2010

  • Random Forests

    Open Access•Leo Breiman•Machine Learning•2001

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    Zachary Hamilton, Alex Kigerl et al.•Justice Quarterly•2022

  • Tailoring to a Mandate

    Zachary Hamilton, Grant Duwe et al.•Justice Quarterly•2022

  • Prisoner Reentry in the Era of Mass Incarceration

    Daniel P Mears, Joshua C Cochran•Prisoner Reentry in the Era of…•2015

  • Artificial Intelligence, Predictive Policing, and Risk Assessment for Law Enforcement

    Richard A Berk•Annual Review of Criminology•2020

  • Effects of Automating Recidivism Risk Assessment on Reliability, Predictive Validity, and Return on Investment (ROI)

    Open Access•Grant Duwe, Michael Rocque•Criminology & Public Policy•2017

  • The Emergence of Machine Learning Techniques in Criminology

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    Open Access•Richard A Berk, Richard Berk et al.•Sociological Methods & Research•2021

  • Evaluation of Random Forest in Crime Prediction

    Gyeongseok Oh, Juyoung Song et al.•Deviant Behavior•2022

Citations per year1
Citation span2026 - 2026 (1)
Highly citedNo

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