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Related Questions
- Can data augmentation help improve the diversity of training datasets and mitigate selection bias?
- How does data augmentation affect the generalizability of machine learning models to real-world scenarios?
- What are some common data augmentation techniques used to address selection bias in image classification tasks?
- In what ways can data augmentation help reduce overfitting to specific subgroups in a dataset?
- Can data augmentation be used to balance the distribution of underrepresented classes in a dataset?
- How does data augmentation impact the performance of machine learning models on out-of-distribution data?
- What are some potential challenges and limitations of using data augmentation to reduce selection bias?
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