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Related Questions
- How do feature permutation methods such as recursive feature elimination (RFE) handle high-dimensional feature spaces in text summarization models?
- Can you explain how SHAP values, specifically SHAP interaction values, account for feature interactions in high-dimensional spaces during text summarization?
- What are the differences between feature permutation and SHAP values in handling high-dimensional feature spaces in text summarization tasks?
- How do feature permutation methods like permutation importance and SHAP values compare in identifying feature importance in high-dimensional feature spaces?
- Can you discuss the limitations of feature permutation and SHAP values in handling high-dimensional feature spaces, especially in text summarization models?
- How do feature permutation methods and SHAP values handle feature correlations and multicollinearity in high-dimensional feature spaces?
- What are some strategies for mitigating the curse of dimensionality when using feature permutation and SHAP values in text summarization tasks?
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