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Related Questions
- What are some key factors that contribute to unstable feature importance scores in machine learning models?
- Can you explain how the selection of hyperparameters affects the calculation of feature importance?
- How do you handle multicollinearity in feature importance calculations to avoid misleading results?
- What are some best practices for interpreting feature importance scores in complex models, such as neural networks?
- Can you discuss the impact of model selection on feature importance scores and how to mitigate any resulting biases?
- What are some common pitfalls when using permutation importance as a method for calculating feature importance?
- How can you use techniques like feature selection or dimensionality reduction to improve the accuracy and interpretability of feature importance scores?
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