This project is about predicting loan defaults based on a dataset that includes information about loans and borrowers. The project uses a pipeline to pre-process the data, balance it using SMOTEENN, and trains several classifiers to predict whether a loan is going to default or not.
To run the project, you need to have the following libraries installed:
- pandas
- numpy
- sklearn
- imblearn
- xgboost
You also need to download the following dataset files:
- Financial Data.csv
- Default Data.csv
After that, you can run the code in loan-default-prediction.ipynb file.
To run this project, you need to have Jupyter Notebook or JupyterLab installed on your machine.
Open the loan-default-prediction.ipynb file in Jupyter Notebook or JupyterLab and run the cells.
This project is licensed under the MIT License - see the LICENSE.md file for details.