P3GM is a differentially private generative model. The algorithm of P3GM is described in our paper (https://arxiv.org/abs/2006.12101).
This code is implemented by python3.7.9.
Install P3GM.
git clone https://github.com/tkgsn/P3GM
cd P3GM
Install tensorflow_privacy library.
git clone https://github.com/tensorflow/privacy.git
Make a virtual enviroment and install the needed dependencies.
python -m venv venv
. venv/bin/activate
pip install -r requirements.txt
Download the datasets.
./download_dataset.sh
Run the experiments.
./exp.sh
Kaggle Credit Dal Pozzolo, Andrea, et al. "Calibrating probability with undersampling for unbalanced classification." 2015 IEEE Symposium Series on Computational Intelligence. IEEE, 2015.
Isolet: https://archive.ics.uci.edu/ml/datasets/isolet
ESR: https://archive.ics.uci.edu/ml/datasets/Epileptic+Seizure+Recognition