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Related Questions
- What are some strategies for dealing with noise in high-dimensional feature spaces?
- Can you explain the concept of feature selection in machine learning and how it relates to permutation importance?
- How does the effect of irrelevant features impact the results of permutation importance?
- In high-dimensional spaces, do methods such as recursive feature elimination perform better than permutation importance?
- Are there any techniques to estimate variable importance in feature spaces where permutation importance may not apply?
- For datasets with highly correlated features, how do permutation feature importance and other importance techniques handle multicollinearity?
- When dealing with datasets containing ordinal features, do you treat them as nominal features and use permutation importance as before, or adjust the model accordingly?
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