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Related Questions
- Can you explain how permutation importance is used to evaluate the contribution of individual features in a machine learning model?
- How do SHAP values help to identify the specific input features that influence a model's predictions?
- What are some common use cases where permutation importance is preferred over SHAP values for feature importance analysis?
- Can you provide an example of how permutation importance is used to identify feature interactions in a complex machine learning model?
- How do SHAP values handle non-linear relationships between features and model predictions compared to permutation importance?
- Can you discuss the trade-offs between using permutation importance and SHAP values for feature importance analysis in terms of computational cost and interpretability?
- In what scenarios is it recommended to use both permutation importance and SHAP values together for a more comprehensive feature importance analysis?
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