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Related Questions
- What are some common evaluation metrics used in machine learning and how do they impact model bias?
- Can you explain the trade-off between precision and recall in model evaluation and how it relates to bias?
- How does the choice of evaluation metric affect a model's decision-making process and potential for bias?
- What are some real-world examples of how biased evaluation metrics have led to biased decision-making in models?
- Can you discuss the concept of 'evaluation metric drift' and how it can affect a model's bias over time?
- How can ensemble methods and model averaging be used to mitigate the impact of biased evaluation metrics on model decision-making?
- What role do evaluation metrics play in ensuring fairness and equity in machine learning models?
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