MIT Computer Science & Artificial Intelligence Laboratory (CSAIL) spin-off DataCebo is offering a new tool, dubbed Synthetic Data (SD) Metrics, to help enterprises compare the quality of machine-generated synthetic data by pitching it against real data sets.
The application, which is an open-source Python library for evaluating model-agnostic tabular synthetic data, defines metrics for statistics, efficiency and privacy of data, according to Kalyan Veeramachaneni, MIT’s principal research scientist and co-founder of DataCebo.
