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Related Questions
- What is class imbalance in machine learning and how is it typically addressed?
- How does class weighting differ from oversampling in handling class imbalance, and what are the benefits of each approach?
- Can you provide a concrete example of when oversampling might be more suitable than class weighting, and vice versa?
- What are some common issues or challenges associated with using class weighting or oversampling in class imbalance problems?
- How do resampling methods like SMOTE and ADASYN work in handling class imbalance, and what are their trade-offs?
- Are there any scenarios where ensemble methods like bagging and boosting are particularly effective for class imbalance problems?
- Can you discuss the importance of evaluating model performance using metrics like precision, recall, and F1-score when dealing with class imbalance?
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