Unverified50% confidenceFactExact time
Average accuracy masks distributional skew; a judge that gets all easy cases right and is overconfident on hard cases can post a high average score while failing at critical points.
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50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
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Related Claims
VerifiedWhen samples are severely imbalanced, Accuracy becomes misleading—a model that predicts everyone as healthy can still achieve an accuracy of over 99%.77% similarUnverifiedIn scenarios with extreme class imbalance (such as fraud detection), looking solely at accuracy as an evaluation metric is completely meaningless.77% similarUnverifiedThe core property of a strictly proper scoring rule is that the expected score is maximized if and only if the forecaster reports the probability they truly believe, with common examples including log-likelihood loss and the Brier score.76% similarUnverifiedCalibration does not equal high accuracy; a system that reports 95% confidence on everything may still be overconfident or blindly optimistic even if its accuracy reaches 95%.76% similarUnverifiedIn class-imbalance scenarios, a model can achieve seemingly impressive accuracy by always predicting the majority class, a phenomenon known as the Accuracy Paradox.75% similar
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