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Related Questions
- What are some common data preprocessing techniques used to address representation bias in machine learning?
- How can feature engineering techniques, such as data normalization and feature scaling, reduce representation bias?
- What role do data augmentation techniques play in mitigating representation bias in image classification tasks?
- Can you explain how handling missing values in a dataset can impact representation bias and how to address it?
- How do techniques like oversampling the minority class and undersampling the majority class affect representation bias?
- What is the impact of data preprocessing on model performance when dealing with imbalanced datasets?
- Can you discuss the trade-offs between data preprocessing techniques and their potential impact on model interpretability?
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