Out With the Old and in With the New? An Empirical Comparison of Supervised Learning Algorithms to Predict Recidivism

Recent research has produced mixed results as to whether newer machine learning algorithms outperform older, more traditional methods such as logistic regression in predicting recidivism. In this study, we compared the performance of 12 supervised learning algorithms to predict recidivism among offe...

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Bibliographic Details
Authors: Duwe, Grant 1971- (Author) ; Kim, KiDeuk (Author)
Format: Electronic Article
Language:English
Published: 2017
In: Criminal justice policy review
Year: 2017, Volume: 28, Issue: 6, Pages: 570-600
Online Access: Volltext (Resolving-System)
Check availability: HBZ Gateway
Keywords:
Machine learning
Predictive discrimination
Calibration
Recidivism
Risk assessment