Counterfactual fairness: Revision history

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19 March 2023

  • curprev 19:1419:14, 19 March 2023‎ Walle talk contribs‎ 4,000 bytes +4,000‎ Created page with "{{see also|Machine learning terms}} ==Introduction== Counterfactual fairness is a concept in machine learning that aims to ensure that an algorithm's predictions are fair by considering hypothetical alternative outcomes under different conditions. The idea is to create models that make unbiased decisions by accounting for potential biases in data, which could lead to unfair treatment of individuals or groups. This concept is particularly important in the context of sensi..."
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