REaLTabFormer
The REaLTabFormer framework utilizes sequence-to-sequence models and GPT-2 to generate realistic relational and tabular data. It's designed for dataset synthesis, handling both relational structures and independent observations effectively. Available on PyPi, REaLTabFormer is easy to install and use, demonstrating excellent performance in prediction tasks. It employs techniques like target masking and statistical bootstrapping to reduce overfitting, with a user-friendly interface for creating validators to ensure high-quality synthetic samples.
