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Related Questions
- What are some common strategies for data augmentation in machine learning?
- How can oversampling the minority class be used to mitigate label imbalance?
- What are the limitations of data augmentation in addressing label imbalance?
- Can you explain the concept of synthetic minority over-sampling technique (SMOTE) in data augmentation?
- How does data augmentation impact the performance of a classification model in the presence of label imbalance?
- What are some techniques for undersampling the majority class to mitigate label imbalance?
- Can you discuss the role of data augmentation in improving the generalizability of a model to unseen data?
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