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Related Questions
- Can data augmentation fully address the issue of label imbalance in imbalanced datasets?
- What are the potential drawbacks of relying solely on data augmentation to address label imbalance?
- How does data augmentation impact the performance of machine learning models on imbalanced datasets?
- Can data augmentation be used in conjunction with other techniques to address label imbalance?
- What are the limitations of data augmentation in terms of generating diverse and realistic augmented data?
- How does the quality of the original data affect the effectiveness of data augmentation in addressing label imbalance?
- Can data augmentation be used to address class imbalance in multi-class classification problems?
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