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Related Questions
- What are some examples of non-linear interactions between features in a machine learning model that are challenging to capture with traditional feature importance metrics?
- Can you provide examples of feature interactions that are hard to identify using SHAP or LIME?
- What are some scenarios where the interaction between two features is more important than the individual feature values themselves?
- How do feature interactions affect the performance of a model when the features are correlated with each other?
- Can you give examples of how feature interactions can lead to biased models and how to mitigate this?
- What are some challenges in capturing complex feature interactions using traditional feature importance metrics like permutation importance?
- How do feature interactions impact the interpretability of a model when the interactions are non-linear or have a high degree of complexity?
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