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Related Questions
- What are the key differences between precision and recall in the context of the F1-score?
- How does the F1-score balance the trade-off between precision and recall?
- What are some common scenarios where the F1-score may not be a suitable evaluation metric?
- Can you provide examples of when the F1-score would be more informative than accuracy or precision?
- How does the F1-score perform in imbalanced datasets, and what are the implications for model selection?
- What are some alternative evaluation metrics that can be used in conjunction with or instead of the F1-score?
- How does the choice of evaluation metric impact the selection of hyperparameters in machine learning models?
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