FAiRDAS_AIforEd

This repository provides the code for reproducing the results obtained in the paper Ensuring Fairness Stability for Disentangling Social Inequality in Access to Education: the FAiRDAS General Framework published at IJCAI24 (AI for Good track).

Prerequisites 📋

• Virtual environment with Python 3.7
• Packages:

  pip install -r requirements.txt
  

How to Run ▶️

The script run.py replicates the results presented in the paper:

python run.py 

Results

Results are stored in results folder.
In particular, the folder results/records contains:

• the configuration file with all the run information config.json
• the historical records of actions, metrics of interest, optimization and ranking (.pkl files)
• the mean and standard deviation of the metrics (statistics.txt and statistics.json)

while the folder results/images contains images both in png and eps format.

MLP Regressor

The MLP regressor has been trained on utils/training_data.csv with script utils/train_regressor.py. The resulting model weights are stored in utils/regressor_checkpoint.pt.

To re-train the regressor, run:

python utils/train_regressor.py

Contacts ✉️

Eleonora Misino: eleonora.misino2@unibo.it