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之前在文章中看到他们总是不懂是什么意思，在仔细查了一番资料之后，特来总结一下。
ROC(Receiver operating characteristic) curves present a visual impression for the accuracy of diagnostic systems and displays the tradeoffs between sensitivity and specificity for various setting of the decision criterion.
ROC曲线表示了诊断系统的精确度，表现出不同设置下的敏感度和特异度的权衡。
在医学上，敏感度表示患病被诊断为阳性的概率，特异度表示无病被诊断为阴性的概率。敏感度和特异度会受到分界点移动的影响。例如下图，当Cut-off移动时，各部分面积都会随之改变。
AUC: The area under the ROC curve gives expression to discrimination capacity for two classes of events.
对分类问题的ROC曲线，AUC表示其分类能力的衡量。
AUC是ROC曲线下的面积，AUC的数值范围从0到1
SROC: A summary receiver operating characteristic (SROC) curve was obtained by constructing regression model using unweighted, weighted, and robust methods.
或许和ROC的区别在ROC是二分类问题上的曲线，SROC是回归问题。
参考资料：
https://zh./wiki/ROC%E6%9B%B2%E7%BA%BF
http://estat./blog/post/61795603-roc%E6%9B%B2%E7%B7%9A-%28receiver-operating-characteristic-curve%29
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