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 a practical application perspective. This task not only focuses on the statistical properties of the data but also emphasizes its performance in specific tasks, ensuring that synthetic data can meet the demands of complex application scenarios. In time series analysis, this evaluation process is particularly important, as it helps enhance the accuracy of model training and predictions.