Predicting recidivism among youth offenders: Augmenting professional judgement with machine learning algorithms.
Journal:
Journal of social work (London, England)
Published Date:
Dec 27, 2017
Abstract
SUMMARY: Offender rehabilitation seeks to minimise recidivism. Using their experience and actuarial-type risk assessment tools, probation officers in Singapore make recommendations on the sentencing outcomes so as to achieve this objective. However, it is difficult for them to maximise the utility of the large amounts of data collected, which could be resolved by using predictive modelling informed by statistical learning methods.
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