Unverified50% confidenceFactExact time
CVaR_α measures the average loss of a random variable in the worst (1-α) fraction of cases; as α→1 it degenerates to the expected value, and as α→0 it approaches the worst-case cost.
1
Sources
50%
Confidence
Long-term
Relevance
9/30/2026
First Seen
Sources
Related Entities
Related Claims
Unverified贝叶斯最优分类器在0-1损失下等价于选择后验概率最大的类别,回归问题中条件期望在平方损失下是最优预测73% similarUnverified线性回归的最小二乘损失与逻辑回归的交叉熵损失分别对应高斯噪声假设与伯努利分布假设下的最大似然估计69% similarVerifiedAUC equals the probability that, when one positive sample and one negative sample are randomly drawn from all positive and negative samples respectively, the predicted score of the positive sample is higher than that of the negative sample.69% similarUnverifiedThe load balancing loss uses the sum of squares of all expert selection frequencies L=ΣFi², and by the Cauchy–Schwarz inequality the loss is minimized when all Fi=1/N.68% similarUnverified困惑度是测试集上每个token平均负对数似然的指数,值越低代表模型对语料的预测越准确68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/961045API
curl https://kongchang.com/api/v1/knowledge/claims/961045MCP
get_claim(id=961045)