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Related Questions
- Can feature permutation importance be used as a filter method in conjunction with other feature selection techniques such as recursive feature elimination (RFE) or correlation-based feature selection (CFS)?
- How does feature permutation importance interact with other feature selection methods, such as wrapper-based methods like forward or backward selection?
- Can feature permutation importance be combined with dimensionality reduction techniques like PCA or t-SNE to improve model interpretability?
- How does feature permutation importance compare to other feature selection methods in terms of its ability to handle high-dimensional data and non-linear relationships between features?
- Can feature permutation importance be used to identify the most informative features for a given target variable, and if so, how does it relate to other feature ranking techniques like mutual information or random forests?
- How can feature permutation importance be used in conjunction with model-agnostic explanations like SHAP or LIME to provide a more comprehensive understanding of model behavior?
- Can feature permutation importance be applied to ensemble models, and if so, how does it account for the interactions between individual models in the ensemble?
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