Code for reproducing results in Delayed Impact of Fair Machine Learning (Liu et al 2018)
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This repository contains code for reproducing experiment results in:

Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt. Delayed Impact of Fair Machine Learning. Proceedings of the 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, 2018.


  1. Clone this repository.
  2. Download the data folder from the Github repository for fairmlbook (Barocas, Hardt and Narayanan 2018), saving it to the root directory of the delayedimpact repository.
  3. Open delayedimpact/notebooks/FICO-figures.ipynb in Jupyter with a Python 3.6 kernel and run all cells.


Part of our implementation is adapted from:

Moritz Hardt, Eric Price, and Nati Srebro. Equality of opportunity in supervised learning. In Proc. 30th NIPS, 2016.


This repository is licensed under the BSD 3-Clause "New" or "Revised" License.