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Related Questions
- Can you explain how to calculate fairness metrics such as demographic parity and equal opportunity for product recommendations?
- What are some common techniques used to evaluate fairness in product recommendations, and how do they relate to feature importance and partial dependence plots?
- How can you use feature importance and partial dependence plots to identify biases in product recommendations and develop strategies to mitigate them?
- What are some challenges associated with evaluating fairness in product recommendations, and how can they be addressed using metrics and techniques?
- Can you discuss the role of interpretability methods, such as SHAP values and LIME, in evaluating fairness in product recommendations?
- How can you use data preprocessing techniques, such as data normalization and feature scaling, to improve the fairness of product recommendations?
- What are some techniques for handling missing values in product recommendation data, and how can they impact fairness evaluation?
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