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                            Library & Multimedia
 NIJ Recidivism Challenge, 2021 - Team Early Stopping,  Years 2 and 3
NCJ Number
              305139

Author(s)
          Team Early Stopping
Date Published

2021
Length
              3 pages
Annotation
              Team Early Stopping presents its recidivism predictions for years 2 and 3 of the parole period for the NIJ Recidivism 2021 Challenge.
Abstract
              Regarding the variables selected for the calculation of recidivism, the team did not include many new features, but rather converted features to ordered numeric values whenever possible. Before fitting the final model, the team fit a series of preliminary boosted tree models to impute missing data and to predict secondary outcomes;  for example, to predict Year 2, the team first predicted Year 3 and Any Year and then used out-of-field predictions for them as input features. The two imputed supplementary targets ended up being the most important variables by a wide margin, which makes sense, given their interrelationships with the primary target. The team used ensembles of gradient boosted tree models from three packages: XGBoost, LightGBM, and Catboost. It used five-fold cross-validation to create out-of-fold predictions, and then a linear model as the second level model to determine final blending weights. The team used Brier Score and Binary Cross Entropy as loss functions and made no special adjustment for male/female or for thresholding. Future considerations are discussed.
      
  
          Additional Details
Grant Number(s)
        Recidivism Forecasting Challenge Winning Paper


  
  
        
  Agencies
        NIJ-Sponsored


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