ConceptCalibrated Confidence / 概率校准

Calibrated Confidence

A core metric for evaluating the quality of a model's probabilistic outputs. A model is considered calibrated when its expressed confidence scores are statistically aligned with actual accuracy rates—for example, predictions made with 70% confidence are correct approximately 70% of the time. Calibrated outputs can be used directly as automation thresholds without requiring additional reliability filtering.

Timeline (last 90 days)

Sep 25

The model's confidence is calibrated, trained via reinforcement learning with strict scoring rules, statistically aligning output probabilities with actual accuracy.

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The model's confidence is calibrated, trained via reinforcement learning with strict scoring rules, statistically aligning output probabilities with actual accuracy.

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