A package to predict loan risk using a decision tree model.
Project description
Loan Risk Predictor
A Python package to predict loan default risk based on applicant data. This project is built from a Kaggle notebook and structured as an installable PyPI package.
Features
- Data preprocessing including cleaning, encoding, and scaling.
- A Decision Tree classification model for risk prediction.
- A simple pipeline to load data and train the model.
Installation
You will be able to install this package from PyPI:
pip install loan-risk-predictor
How to Use
After installation, you can run the training pipeline directly from the command line:
python -m loan_risk_model.train
Project Structure
loan-risk-predictor/ │ ├── loan_risk_model/ │ ├── data/ │ │ └── training.csv │ ├── init.py │ ├── data_preprocessing.py │ ├── model.py │ └── train.py │ ├── notebooks/ │ └── Your-Kaggle-Notebook.ipynb │ └── ... (packaging files)
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