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Related Questions
- What are the primary benefits of using synthetic data to address label imbalance in machine learning models?
- How does synthetic data help to improve model performance in imbalanced datasets?
- What are the potential drawbacks of relying on synthetic data to address label imbalance?
- Can synthetic data be used to augment existing datasets, and if so, how does it impact model performance?
- How does the quality of synthetic data affect the overall performance of a machine learning model?
- Are there any scenarios where synthetic data is not suitable for addressing label imbalance?
- Can synthetic data be used to address class imbalance in multi-class classification problems?
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