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Related Questions
- Can feature importance metrics accurately capture nonlinear relationships between variables?
- How do feature interactions affect the interpretation of feature importance in machine learning models?
- What are some common pitfalls to avoid when using feature importance metrics in the presence of correlation versus causation?
- In what scenarios do feature importance metrics tend to overestimate or underestimate the contribution of individual features?
- How can feature interactions lead to false positives or false negatives in feature importance metrics?
- What techniques can be used to identify and account for feature interactions when interpreting feature importance?
- Can feature importance metrics be used to identify redundant or irrelevant features in the presence of feature interactions?
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