Combining Machine Learning and Queueing Theory for Data-Driven Incarceration-Diversion Program Management
Bingxuan Li,
Antonio Castellanos,
Pengyi Shi
et al.
Abstract:Incarceration-diversion programs have proven effective in reducing recidivism. Accurate prediction of the number of individuals with different characteristics in the program and their program outcomes based on given eligibility criteria is crucial for successful implementation, because this prediction serves as the foundation for determining the appropriate program size and the consequent staffing requirements. However, this task poses challenges due to the complexities arising from varied outcomes and lengths… Show more
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