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Related Questions
- Can feature permutation importance methods handle interactions between numerical and categorical features?
- How do feature permutation importance methods account for non-linear relationships between features of different data types?
- Do feature permutation importance methods require any specific preprocessing or transformation for handling non-linear relationships between numerical and categorical features?
- Can feature permutation importance methods handle non-linear relationships between high-dimensional numerical features?
- How do feature permutation importance methods compare to other methods for handling non-linear relationships between features, such as partial dependence plots?
- Can feature permutation importance methods be used to identify non-linear relationships between features in a high-dimensional dataset?
- Do feature permutation importance methods provide any insights into the nature of non-linear relationships between features, such as the presence of interactions or nonlinear effects?
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