Unverified50% confidenceFactExact time
AURC focuses on error frequency but treats all errors as equivalent, whereas UtilityAUC introduces utility weights so that high-cost errors account for a larger share in the curve integral.
1
Sources
50%
Confidence
Long-term
Relevance
10/20/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedIn class-imbalanced scenarios, Accuracy is misleading, and Precision-Recall curves and AUC-ROC are more reliable performance measurement tools.69% similarUnverifiedCalculator errors are usually input errors or overflow, whereas evaluating AI reliability is far more complex than for calculators.66% similarUnverifiedAn error budget is a systematic analysis method that decomposes the total accuracy specification layer by layer into individual error sources (such as Abbe error, thermal expansion, vibration, sensor nonlinearity, actuator resolution, etc.) and assigns an acceptable upper limit to each.65% similarUnverified如果参数量充足的模型连几十个样本都无法记住，几乎可以断定存在硬性错误，如标签错位、损失函数计算错误、梯度未正确回传等64% similarUnverified数值实验表明三项误差中score误差项占据主导，整体TV误差与score误差呈线性关系64% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1073854API
curl https://kongchang.com/api/v1/knowledge/claims/1073854MCP
get_claim(id=1073854)