A Comparison of Logistic Regression, Classification and Regression Tree, and Neural Networks Models in Predicting Violent Re-Offending

By Yuan-yuan Liu, Min Yang, Malcolm S. Ramsay, Xiao Li, Jeremy Coid. 2011

109 citations recorded by the source corpus.

Subfields: Clinical Psychology, Sociology and Political Science

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Clinical Psychology

1. Richard A. Berk

In Sociology and Political Science

1. Aaron Roth
2. Michael Kearns
3. Hoda Heidari
4. Shahin Jabbari
5. Richard A. Berk
6. P. V. D. van der Heijden
7. Cynthia Rudin
8. Dana Pessach

Citations in the corpus

• Fairness in Criminal Justice Risk Assessments: The State of the Art (2017, methodology): “…ongoing discussions about how much better in practice risk assessments derived from machine learning perform compared to risk assessments derived from older, conventional methods (Liu et al., 2011; Berk, 2012; Berk and Bleich, 2013; Brennan and Oliver, 2013; Rhodes, 2013; Ridgeway, 2013a; 2013b).”
• Which method predicts recidivism best?: a comparison of statistical, machine learning and data mining predictive models (2013, background): “The most recent study that compared techniques in the recidivism domain was from Yang et al. (2011).”