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Related Questions
- How do SHAP values consider interactions between features when calculating the contribution of each feature to the model's prediction?
- Can you explain the difference in handling non-linearity between SHAP values and permutation importance?
- How do SHAP values account for non-linear relationships between features and model predictions compared to feature permutation methods?
- In what scenarios is SHAP more effective than permutation importance in capturing non-linearity in the relationships between features and model predictions?
- How do SHAP values handle feature correlations and non-linear relationships between features and model predictions?
- Can you provide an example of a scenario where SHAP values outperform permutation importance in capturing non-linear relationships between features and model predictions?
- What are the limitations of permutation importance in handling non-linear relationships between features and model predictions compared to SHAP values?
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