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Related Questions
- Can partial dependence plots be misleading when the relationship between a feature and the predicted outcome is non-linear or involves interactions between multiple features?
- In what cases do partial dependence plots fail to capture the importance of features that have a non-monotonic relationship with the predicted outcome?
- How do partial dependence plots perform when dealing with high-dimensional feature spaces or models with many irrelevant features?
- Can partial dependence plots accurately represent feature importance in models with non-linear relationships or complex interactions?
- What are some common pitfalls or limitations of using partial dependence plots to understand feature importance in complex models?
- Can partial dependence plots be used to identify feature importance in models with many correlated features?
- In what situations do partial dependence plots provide a biased representation of feature importance due to the model's underlying assumptions or implementation details?
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