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Related Questions
- Can feature engineering techniques such as data augmentation or oversampling help improve the performance of machine learning models on imbalanced datasets?
- How does the choice of feature engineering methods affect the accuracy and fairness of machine learning models on imbalanced datasets?
- Can feature engineering be used to identify and remove irrelevant or redundant features that may exacerbate class imbalance?
- How does feature engineering impact the interpretability of machine learning models on imbalanced datasets?
- Can feature engineering techniques such as dimensionality reduction or feature selection help mitigate the effects of class imbalance?
- How does the interaction between feature engineering and algorithmic choices impact the performance of machine learning models on imbalanced datasets?
- Can feature engineering be used to create new features that capture the underlying relationships between variables and classes, improving model performance on imbalanced datasets?
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