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Related Questions
- Can you explain how interpretability and model performance are often inversely related in context-aware metrics?
- How does the choice of evaluation metrics affect the trade-off between interpretability and model performance?
- What role does domain knowledge play in identifying the most relevant context-aware metrics for a particular application?
- How can domain experts use their knowledge to design more interpretable models without sacrificing performance?
- What are some common pitfalls to avoid when trying to balance interpretability and model performance in context-aware metrics?
- Can you provide examples of successful applications that have effectively balanced interpretability and model performance in context-aware metrics?
- How can the use of domain knowledge help identify potential biases in context-aware metrics and mitigate their impact on model performance and interpretability?
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