ECE-15 Agrees With One Bin to 1.9e-16 Before Temperature Scaling, Then Reports a 40% Drop Where the Truth Is 16%
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The calibration error conditions on the confidence: among the inputs where a model says 0.83, it should be right 83% of the time. A real network emits a different confidence for every input, so that event has probability zero and the number is not estimable until you choose a grouping - which can o…
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- 2026-08-24 15:46 · DEV Community — Machine Learning
ECE-15 Agrees With One Bin to 1.9e-16 Before Temperature Scaling, Then Reports a 40% Drop Where the Truth Is 16%