This repository contains the code for the paper Individually Fair Gradient Boosting by Vargo et al. The paper appeared at ICLR 2021.

• FOR AN EXAMPLE OF BuDRO, SEE THE NOTEBOOK german/01_german_run.ipynb
• FOR A SIMPLE EXAMPLE OF BuDRO ON SYNTHETIC DATA, SEE THE SCRIPT synthetic/sim_tf_test.py - THE RESULTS CAN BE PLOTTED IN synthetic/simulated-plots.ipynb TO PRODUCE AN EQUIVALENT TO FIGURE 1 IN THE SUPPLEMENT

The packages used in the conda environment for the notebooks and scripts are in the file py37fair.yml. You also need to install the AIF360 package (from "https://github.com/IBM/AIF360") and probably the SenSR package (from "https://github.com/IBM/sensitive-subspace-robustness).

In most files, all paths have been removed and need to be replaced with your own paths.

Other directories:

german contains specific scripts and notebooks used in the experiements on the German credit data set.

adult contains specific scripts and Jupyter notebooks used in the experiments on the Aadult data set.

compas contains specific scripts and notebooks used in the experiments on the COMPAS data set.

scripts contains the files needed for running BuDRO, as well as a few other scripts used in data processing.

synthetic contains the scripts needed to generate the synthetic plots from the appendix of the submission. To plot the data generated in this directory, see the notebook simulated-plots.ipynb.