The SDMetrics library welcomes contributions for new metrics!
The SDMetrics library counts fairness, accuracy and explainability as our top values.
SDMetrics is a model-agnostic library. Anyone who has real and synthetic data can use the library, no matter where or how the synthetic data was generated.
The SDMetrics library is verified by thousands of users across the globe. The core maintenance team includes MIT alums and AI researchers, here to ensure that metrics and reports can be trusted.
SDMetrics is moving towards intuitive, easily explainable metrics and reports. With years of experience in deployable machine learning systems, we understand that clear communication of simple metrics can make or break your synthetic data project.