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Related Questions
- What are the underlying assumptions of demographic parity and equalized odds metrics in fairness evaluation?
- How do the demographic parity and equalized odds metrics differ in terms of their fairness criteria?
- Can you provide an example use case where demographic parity metric would be more suitable than equalized odds metric?
- What are the advantages of using equalized odds metric over demographic parity metric in certain scenarios?
- How do demographic parity and equalized odds metrics address disparate impact in machine learning models?
- What are the key differences in the calculation and interpretation of demographic parity and equalized odds metrics?
- Can you explain why equalized odds metric is considered more comprehensive than demographic parity metric in assessing fairness?
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