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How wrong is a model's confidence?

This story is from 2026-10-28. It is preserved in the archive; the latest stories are on the live feed.

A ResNet-34 trained on CIFAR-100 is measurably overconfident: its top prediction bin claims 99% certainty while landing correctly only 94% of the time. Temperature scaling, a single learned number, cuts that gap by nearly two-thirds without changing a single prediction. Key takeaways A registered g…

Read the full story at DEV Community — Machine Learning ↗

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  1. 2026-10-28 06:26 · DEV Community — Machine Learning
    How wrong is a model's confidence?

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