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Related Questions
- What are some common metrics used to evaluate fairness in machine learning models?
- How do you account for multiple sensitive attributes in fairness evaluation?
- Can you describe techniques for detecting and mitigating bias in models with multiple sensitive attributes?
- What is the difference between group fairness and individual fairness in the context of multiple sensitive attributes?
- How do you ensure that your model is fair when dealing with multiple sensitive attributes such as age, gender, and income?
- What are some challenges in evaluating fairness in models that involve multiple sensitive attributes?
- Can you explain how to use techniques such as statistical parity and equalized odds to evaluate fairness in models with multiple sensitive attributes?
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