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Related Questions
- Can dimensionality reduction techniques like PCA or t-SNE affect the performance of machine learning models on imbalanced datasets?
- How do feature selection techniques like mutual information or recursive feature elimination impact the class balance in imbalanced datasets?
- Do techniques like feature scaling or normalization have a significant impact on the performance of machine learning models on imbalanced datasets?
- Can feature engineering techniques like binning or discretization improve or worsen the performance of machine learning models on imbalanced datasets?
- How do feature interactions, such as polynomial or interaction terms, affect the performance of machine learning models on imbalanced datasets?
- Can dimensionality reduction techniques like singular value decomposition (SVD) or independent component analysis (ICA) help mitigate the effects of class imbalance?
- Do feature engineering techniques like encoding categorical variables or one-hot encoding impact the performance of machine learning models on imbalanced datasets?
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