https://tracholar.github.io/machine-learning/2018/01/26/auc.html
https://blog.csdn.net/qq_22238533/article/details/78666436
y轴： tpr = tp/p
x轴: fpr = fp/n
正样本中取出样本预估为正的概率 > 负样本中取出负样本为正的概率
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正样本排在负样本前面
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排序性好。
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计算auc
https://blog.csdn.net/qq_22238533/article/details/78666436
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roc 曲线
纵轴刻度间隔设为1/p，横轴设为1/n；按照score倒排，遇到真实正例y+1，遇到真实负例x+1
https://stats.stackexchange.com/questions/145566/how-to-calculate-area-under-the-curve-auc-or-the-c-statistic-by-hand
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