Linking prediction and prevention

By Greg Ridgeway. 2013

How researchers see this paper

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

1. Richard A. Berk
2. Justin Bleich
3. G. Barnes
4. Adam Kapelner
5. E. Kurtz
6. J. Henderson
7. Jiaming Zeng
8. Jordan M. Hyatt

Citations in the corpus

• Fairness in Criminal Justice Risk Assessments: The State of the Art (2017, neutral): “…been ongoing discussions about how much better in practice risk assessments derived from machine learning perform compared to risk assessments derived from older, conventional methods (Berk 2012; Berk and Bleich 2013; Brennan and Oliver 2013; Liu et al. 2011; Rhodes 2013; Ridgeway 2013a, 2013b).”
• Using Regression Kernels to Forecast A Failure to Appear in Court (2014, background): “…is now strong evidence that more accurate forecasts can be obtained directly from machine learning procedures (Berk, 2012; Berk and Bleich, 2013; Ridgeway, 2013; Bushway, 2013) such as random forests (Breiman, 2001), stochastic gradient boosting (Friedman, 2002), Bayesian additive regression…”