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Related Questions
- How do permutation importance and SHAP values account for feature interactions in text summarization models?
- What are the key assumptions made by permutation importance and SHAP values in identifying biased features in text summarization models?
- Can you explain how permutation importance and SHAP values handle categorical and numerical features differently in text summarization models?
- How do permutation importance and SHAP values compare in terms of computational efficiency and interpretability in text summarization models?
- What are some common pitfalls to avoid when using permutation importance and SHAP values to detect biases in text summarization models?
- Can you provide examples of how permutation importance and SHAP values can be used to identify biased features in text summarization models?
- How do permutation importance and SHAP values relate to other feature importance methods, such as LIME and partial dependence plots, in text summarization models?
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