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Related Questions
- Can you explain the concept of fairness in machine learning models and why it's essential to evaluate?
- How do you interpret the results of a partial dependence plot, and what are its limitations?
- What are some common metrics used to evaluate fairness in machine learning models, such as disparate impact and equal opportunity scores?
- How do you use SHAP values to identify biased features in a machine learning model?
- Can you compare and contrast the techniques of data preprocessing and feature selection for improving fairness in machine learning models?
- What are the differences between local and global fairness in machine learning models, and which one is more important?
- Can you discuss the role of regularization techniques, such as L1 and L2 regularization, in promoting fairness in machine learning models?
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