Repository for the master's dissertation at SGH Warsaw School of Economics
Title: Machine learning in credit scoring: A fairness approach
Author: Jose Caloca
The workflow is divided in 4 jupyter notebooks:
- descriptive_stats.ipynb
- dataset_preparation.ipynb
- hyperparameter tuning.ipynb
- fairness_pipeline.ipynb
The functions used for the calculations are saved in a the following path: ./utils/fairness_functions.py