Synthetic Data Generation

Synthetic Data Generation refers to the creation of synthetic data through algorithms and techniques that possess similar statistical characteristics to real data. This task aims to address issues such as data privacy protection, data scarcity, and data imbalance, providing reliable data support for training machine learning models, data analysis, and testing. The generated synthetic data can be widely applied in fields like healthcare, finance, and scientific research, enhancing data usability and model performance.