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Related Questions
- Can you explain how feature permutation importance helps to detect non-linear relationships between features and the target variable?
- How does feature permutation importance account for interactions between multiple features that may influence the target variable?
- In what scenarios does feature permutation importance become less effective in capturing complex relationships between features and the target variable?
- Can you provide an example of a dataset where feature permutation importance would struggle to capture the true relationships between features and the target variable?
- How does feature permutation importance differ from other methods, such as recursive feature elimination or recursive feature elimination with cross-validation?
- Can you describe the relationship between feature permutation importance and the concept of feature importance in general?
- How does feature permutation importance handle high-dimensional feature spaces and the curse of dimensionality?
- Can you discuss the limitations of feature permutation importance in terms of scalability and computational efficiency?
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