Can synthetic data help in the accuracy of prediction models?
Yes, synthetic data can indeed help improve the accuracy of prediction models in certain situations. Here's an overview of how synthetic data can be beneficial:
Augmenting limited datasets:
- When real-world data is scarce, synthetic data can increase the training set size
- Helps models learn more robust patterns and generalize better
Balancing imbalanced datasets:
- Generate additional examples for underrepresented classes
- Improves model performance across all categories
Privacy preservation:
- Allows training on sensitive data without exposing real individuals' information
- Useful in healthcare, finance, and other fields with strict privacy regulations