Unverified60% confidenceFactExact time
AUC是二分类模型的综合评估指标,值域0.5到1.0,不受样本类别不平衡影响;临床预测中AUC 0.7~0.8有一定参考价值,0.8~0.9为良好,0.9以上为优秀
2
Sources
60%
Confidence
Long-term
Relevance
7/20/2026
First Seen
Sources
Related Claims
UnverifiedAUC-ROC的核心优势在于对类别不平衡不敏感,能反映模型在不同分类阈值下的综合区分能力,AUC值范围在0.5到1.0之间81% similarUnverifiedAUC是衡量二分类模型综合性能的核心指标,0.5代表随机猜测,1.0代表完美分类81% similarUnverifiedAUC的取值范围在0到1之间,数值越大代表模型分类能力越强80% similarVerified业界通用标准中,AUC > 0.9为优秀,0.8~0.9为良好,0.7~0.8为一般,0.5~0.7为较差,0.5等同于随机猜测78% similarUnverifiedAUC值域为0.5到1.0,0.5代表随机猜测、1.0代表完美预测,不受样本类别不平衡影响76% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/567694API
curl https://kongchang.com/api/v1/knowledge/claims/567694MCP
get_claim(id=567694)