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Related Questions
- What are some alternative evaluation metrics that can be used to improve interpretability of AI models?
- In what ways can overemphasizing accuracy and F1-score lead to a lack of understanding of AI model decision-making processes?
- How can the use of metrics like accuracy and F1-score hinder the development of explainable AI?
- What are some techniques for evaluating AI model interpretability that go beyond traditional metrics like accuracy and F1-score?
- Can you explain how the overreliance on metrics like accuracy and F1-score can lead to a lack of trust in AI model outputs?
- How can the use of multiple evaluation metrics, including those that promote interpretability, improve the transparency of AI models?
- What are some best practices for using metrics like accuracy and F1-score in conjunction with other evaluation metrics to improve AI model interpretability?
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