Minimax loss: Revision history

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20 March 2023

  • curprev 11:4311:43, 20 March 2023‎ Walle talk contribs‎ 2,229 bytes +2,229‎ Created page with "{{see also|Machine learning terms}} ==Minimax Loss== The minimax loss, also known as the minimax regret, is a performance measure in machine learning and game theory that quantifies the worst-case performance of an algorithm or decision rule under uncertainty. This concept is utilized in various optimization problems, where the goal is to minimize the maximum possible loss or regret under uncertain conditions. ===Definition=== Given a decision-making problem, th..."
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