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                            Library & Multimedia
 National Institute of Justice Recidivism Challenge Report: Team Aurors
NCJ Number
              305053

Author(s)
          Team Aurors
Date Published

2021
Length
              18 pages
Annotation
              This report was submitted by Team Aurors as a participant in the U.S. Justice Department’s National Institute of Justice’s (NIJ’s) Recidivism Forecasting Challenge, which aimed to improve the ability to forecast recidivism.
Abstract
              The work reported by the Aurors Team addresses forecasting models that include regression analysis methods (binary logit and LASSO regressions) and machine learning techniques (random forest), combined through a model averaging procedure. The output consists of the percent likelihood of individuals recidivating within one, two, or three years from release. Although this report explains the database construction process and the modeling approach, the results focus on the section of female parolees recidivating within 3 years, since that is the category for which the Aurors team came in second place.
      
  
          Additional Details
Grant Number(s)
        NIJ Recidivism Forecasting Challenge Winning Paper


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Publication Type
        Research (Applied/Empirical)
    
  
  
Date Published: January 1, 2021
    
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