Learning Augmented Robust Algorithmic Recourse

This is a joint work of Kshitij Kayastha, Shahin Jabbari, and Vasilis Gkatzelis.

Installation instructions

1. Clone the repo.

2. Create and activate a virtual environment

cd "LearningAugmentedRobustRecourse"
python -m venv .env
source .env/bin/activate

3. Install the dependencies

pip install requirements.txt

Reproducing Results

You can replicate the experiments described in the paper by running the notebooks in the experiments/ directory.

Inside each of these notebooks, you can specify the dataset and the base model.

Datasets

• German Credit Dataset

  • Link: https://archive.ics.uci.edu/dataset/144/statlog+german+credit+data
  • Features used: duration, amount, age, personal_status_sex.

• Small Business Dataset

  • Link: https://www.kaggle.com/datasets/larsen0966/sba-loans-case-data-set
  • Features used: Zip, NAICS, ApprovalDate, ApprovalFY, Term, NoEmp, NewExist, CreateJob, RetainedJob, FranchiseCode, UrbanRural, RevLineCr, ChgOffDate, DisbursementDate, DisbursementGross, ChgOffPrinGr, GrAppv, SBA_Appv, New, RealEstate, Portion, Recession, daysterm, xx.