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Related Questions
- What are the common causes of class imbalance in active learning, and how can they be addressed?
- How does class imbalance affect the trade-off between precision and recall in active learning, and what are the implications for model performance?
- What are some strategies for rebalancing the classes in active learning, and which ones are more effective?
- Can you explain the concept of oversampling the minority class and undersampling the majority class as a method for addressing class imbalance?
- How does the choice of metric (e.g. accuracy, precision, recall) impact the trade-off between precision and recall in active learning, particularly in the presence of class imbalance?
- What are some techniques for handling class imbalance in active learning, such as SMOTE, ADASYN, and ensemble methods?
- Can you discuss the role of class imbalance in active learning and how it affects the selection of unlabeled data for annotation?
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