Welcome to the complete beginner's guide to GENCDA, a GEnerative method based on Nonlinear Causal Discovery with Apriori! If you're looking for a comprehensive guide to our approach, then you've come to the right place.
For example usage of:
The packages requires a python version >=3.8, as well as some libraries listed in requirements file. For some additional functionalities, more libraries are needed for these extra functions and options to become available.
git clone https://github.com/marti5ini/GENCDA.git
cd GENCDA
Dependencies are listed in requirements.txt, a virtual environment is advised:
python3 -m venv ./venv # optional but recommended
pip install -r requirements.txt
Please note that in addition to the dependencies listed in the requirements file, you also need to install a novel version of "fim" package. You can find the package and installation instructions on the following webpage: https://borgelt.net/pyfim.html
@inproceedings{cinquini2021boosting,
title={Boosting synthetic data generation with effective nonlinear causal discovery},
author={Cinquini, Martina and Giannotti, Fosca and Guidotti, Riccardo},
booktitle={2021 IEEE Third International Conference on Cognitive Machine Intelligence (CogMI)},
pages={54--63},
year={2021},
organization={IEEE}
}