Synthetic Data Evaluation

The Synthetic Data Evaluation task aims to assess the quality of synthetic data through machine learning metrics, thereby measuring its effectiveness and reliability from the perspective of its application in real-world tasks. This task not only helps ensure a high degree of similarity between synthetic and real data but also optimizes the performance of data-driven models, enhancing their generalization capabilities across various application scenarios. As part of the Miscellaneous task, it holds significant value in the fields of data science and artificial intelligence.