Unverified50% confidenceOpinionExact time
膨胀、过时、充满噪声的评估集比没有评估集更糟糕，因为它会给出误导性的信号
1
Sources
50%
Confidence
Long-term
Relevance
8/21/2026
First Seen
Sources
Related Claims
UnverifiedHigh bias means the model is too simple and leads to underfitting, while high variance means the model has learned noise and leads to overfitting, and the two tend to trade off against each other.79% similarVerifiedThe generalization error of a model equals the squared bias plus variance plus irreducible noise.75% similarUnverified当标注不一致存在时，增加更多数据只会成倍放大混乱，向模型提供自相矛盾的监督信号74% similarUnverifiedBatch normalization layers have highly noisy statistical estimates in small-batch scenarios, and combined with the region-level computation characteristics of Dice loss, this amplifies fluctuations in the predicted probability distribution.72% similarUnverified过度膨胀的上下文会稀释模型注意力、抬高推理成本，甚至引入噪声导致幻觉72% similar
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