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Identifying, measuring, and mitigating individual unfairness for supervised learning models and application to credit risk models
Furthermore, we developed a second metric (distinct from the fair similarity metric) to determine how fairly a model is treating similar individuals.
Is Shapley Explanation for a model unique?
Our assessment is that Shapley value for particular feature not only depends on its expected mean but on other moments as well such as variance and there are disagreements for baseline prediction, disagreements for signs and most important feature for different outcomes such as probability, log odds, and binary decision generated using same linear probability model (logit/probit).
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