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Calibrated probability is a foundational concept in statistics and machine learning; commonly used measurement metrics include reliability diagrams and expected calibration error (ECE), and commonly used post-processing calibration methods include Platt scaling, Isotonic regression, or temperature scaling.
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10/16/2026
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