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Related Questions
- What are the common evaluation metrics used to measure model performance, and how do they account for uncertainty and confidence?
- How do metrics such as mean squared error and mean absolute error handle uncertainty in model predictions?
- Can you explain the concept of calibration in machine learning and how it relates to model confidence?
- What is the difference between a model's confidence and its actual accuracy, and how can evaluation metrics capture this difference?
- How do metrics such as Brier score and log loss account for uncertainty and confidence in model predictions?
- Can you discuss the trade-off between precision and recall in evaluation metrics, and how it relates to model uncertainty?
- How do evaluation metrics handle class imbalance in datasets, and what impact does it have on model confidence and uncertainty?
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