SilenceX12138/TabStruct

This tool helps researchers and practitioners evaluate how well synthetic tabular data generation methods preserve the underlying structure and characteristics of real-world datasets. You provide real tabular data and various synthetic data generation models, and it outputs comprehensive evaluation metrics including structural fidelity, privacy preservation, and how well machine learning models trained on the synthetic data perform. Data scientists, machine learning researchers, and anyone working with synthetic data for privacy or augmentation would find this useful.