Welcome to SDGym!
The Synthetic Data Gym (SDGym) is a Python library for benchmarking different synthetic data generators. For example you can compare synthesizers that use classical statistics versus those that use deep learning.
The past few years have seen an increasing amount of research in the synthetic data space. With such a variety of models available, we feel that it's important to validate new techniques with a proper framework in place.
We built SDGym as flexible and customizable framework that you can use for a thorough analysis of synthetic data. This will give you the confidence when publishing your results and incorporating synthetic data into your projects.
If your goal is to test a robust synthetic data model, relying on a single dataset may not give you much confidence. The SDGym library comes with a variety of publicly available datasets that are immediately for use.
This is helpful for detecting errors in your synthesizer as well as identifying its strengths and weaknesses.
We recognize that benchmarking may not be a one-size-fits-all solution. Our framework allows you to input your own custom datasets if you are working with private data.
results = sdgym.benchmark_single_table()
Last modified 6mo ago