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Related Questions
- Can you explain how feature importance plots can help identify biased features in machine learning models?
- How do partial dependence plots help in understanding the relationship between a specific feature and the predicted outcome, and how can this be used to address fairness issues?
- What are some common pitfalls to avoid when using feature importance and partial dependence plots to identify fairness issues in machine learning models?
- Can you provide examples of how feature engineering efforts can be prioritized using feature importance and partial dependence plots?
- How can feature importance and partial dependence plots be used to identify and address issues related to feature interaction and non-linear relationships?
- What role can feature importance and partial dependence plots play in evaluating the fairness of machine learning models in high-stakes applications?
- Can you discuss the relationship between feature importance, partial dependence plots, and model interpretability, and how they can be used together to address fairness issues?
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