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Related Questions
- What are the main differences between oversampling and undersampling in addressing class imbalance in datasets?
- How can oversampling be used to increase the representation of the minority class in a dataset?
- What are some common techniques used for oversampling, such as SMOTE and ADASYN?
- Can undersampling be used to reduce the size of the majority class in a dataset, and how does it affect model performance?
- What are some potential drawbacks of oversampling and undersampling, such as overfitting and loss of information?
- How can ensemble methods, such as bagging and boosting, be used to address class imbalance in datasets?
- What are some real-world applications of class imbalance correction, such as in medical diagnosis and credit risk assessment?
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