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Related Questions
- How do different feature permutation importance metrics handle categorical and continuous features?
- Can you explain the implications of using permutation importance on high-cardinality categorical features?
- How does the choice of metric affect the interpretation of feature importance for mixed-type features?
- In what cases might permutation importance metrics be biased for mixed-type features?
- Can you provide examples of feature permutation importance metrics that are well-suited for mixed-type features?
- How do different machine learning algorithms handle feature interactions when calculating permutation importance?
- What are the limitations of permutation importance when dealing with highly correlated features?
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