Recidivism Forecasting Challenge

You can find the contest details here

  • Predicted recidivism using person and place-based variables with the goal of improving outcomes for those serving a community supervision sentence.
  • Utilised Xgboost, Adaboost, LightGBM, CatBoost, Autoencoder, and Logistic Regression algorithms using Python libraries.
  • Prizewinner of Machine Learning Contest hosted by National Institute of Justice ($19,500).