This code was developed as a study tool for the Cluster Analysis, Association Mining, and Model Evaluation course provided by the University of California Irvine on Coursera. It utilizes the BitcoinHeistRansomwareAddress data set, available at the UCI Machine Learning Repository.
- Clone repository
- Fetch dataset (data.zip)
- Extract inside
{PROJECT_ROOT}/assets/datasetso you have the following:{PROJECT_ROOT}/assets/dataset/BitcoinHeistData.csv
- Install requirements:
pip install -r requirements.txt
- Run
bitcoin_heistmodule for the regular (29 clusters) or for binary classification (2 clusters):python -m bitcoin_heistpython -m bitcoin_heist binary
- Check results under
/assets/results/
Special thanks to Cuneyt Gurcan Akcora (University of Manitoba), Yulia Gel (University of Texas at Dallas), and Murat kantarcioglu (University of Texas at Dallas) for providing the data set used here.
I'd also like to thank University of California Irvine for hosting the UCI Machine Learning Repository, where the data set can be downloaded.