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Reproducing the Paper

If reproducing the experiments in the paper, we recommend creating a separate Conda environment:

git clone https://github.com/MLforHealth/predictive_checklists
cd predictive_checklists/
conda env create -f environment.yml
conda activate ip_checklists

Then, follow the instructions in the README to download and install CPLEX Optimization Studio.

To reproduce the experiments in the paper which involve training grids of checklists using different methods, use scripts/sweep.py as follows:

python -m scripts.sweep launch \
    --experiment {experiment_name} \
    --output_dir {output_root} \
    --command_launcher {launcher}

where:

  • experiment_name corresponds to experiments defined as classes in scripts/experiments.py
  • output_root is a directory where experimental results will be stored.
  • launcher is a string corresponding to a launcher defined in scripts/launchers.py (i.e. slurm or local).

We are not able to provide any data (other than UCI Heart) due to privacy reasons. Instructions for accessing the datasets used in the paper can be found in Appendix D.