/GENCDA

Boosting Synthetic Data Generation with Effective Nonlinear Causal Discovery

Primary LanguageJupyter NotebookMIT LicenseMIT

GENCDA

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.

Tutorial

For example usage of:

Setup

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