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Related Questions
- How do precision and recall differ in the context of class imbalance in active learning, and why is F1-score often used as a compromise between the two?
- What are the implications of class imbalance on the trade-off between precision and recall in active learning, and how can it be addressed?
- Can you explain how the F1-score is calculated and why it's used in class-imbalanced datasets in active learning?
- In active learning, what are the key factors that contribute to the trade-off between precision and recall when dealing with class imbalance?
- How does the choice of evaluation metric affect the active learning strategy in class-imbalanced datasets, and why is it crucial to consider this trade-off?
- Can you discuss the relationship between the trade-off between precision and recall in active learning and the concept of class imbalance, and how to mitigate the former?
- In what ways can active learning strategies be adapted to address the trade-off between precision and recall in class-imbalanced datasets, and what are the benefits of doing so?
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