AUC (Area Under Curve) 被定义为ROC曲线下的面积,显然这个面积的数值不会大于1。又由于ROC曲线一般都处于y=x这条直线的上方,所以AUC的取值范围一般在0.5和1之间。使用AUC值作为评价标准是因为很多时候ROC曲线并不能清晰的说明哪个分类器的效果更好,而作为一个数值,对应AUC更大的分类器效果更好。 从AUC判断分类...
AUC(area under ROC curve), 即 ROC 曲线下方的面积  ROC与P-R关系 PR曲线和ROC曲线有什么联系和不同? 相同点: 首先从定义上PR曲线的R值是等于ROC曲线中的TPR值, 都是用来评价分类器的性能的. 不同点: ROC曲线是单调的而PR曲线不是(根据它能更方便调参), 可以用AUC的值得大小来评价分类器的好坏(是...
The validity of the admission test was analysed using specificity, sensitivity, positive and negative likelihood ratios (LH+, LH), receiver operating characteristic (ROC) curves, area under the ROC curve (AUC), and relative (95% CI). The results showed that the admission test appeared to be ...
Along with the ROC curves, which show the True Positive Rate = TP T P +F N plot- ted against the False Positive Rate = F FP P +T N , we also re- port the Area Under Curve (AUC) and the maximum F- measure ( 2·Precision·Recall Precision+Recall ) as performance measures. 4.1...
(G) ROC curve and the AUC of risk score classification in the TCGA-LIHC dataset. (H) Kaplan–Meier survival curve distribution of risk score in the TCGA-LIHC dataset. Full size image Further better understanding the prognostic model based on 6 NK cell-related genes, we calculated the ...
ROC curves showed that GPC1-positive exosomes in peripheral blood displayed higher area under the curve (AUC) than CA19-9 in peripheral blood (Figure 4). Table 3. Diagnosis values of GPC1 positive exosomes, CA19-9 and EUS-FNA TestSensitivity (95% CI)Specificity (95%CI)Positive predictive...
For instance, Hu et al., integrated lncRNAs SPRY4-IT1, ANRIL and NEAT1 in their studies on nonsmall-cell lung cancer and obtained a specificity of 92.3%, a sensitivity of 82.8%, and an AUC (ROC) (area under the ROC curve - receiver operating characteristic) of 0.87661 (Table 1). ...
Instead, AUC, ROC,... dominates while the model does often need to watch out model drivers. In traditional models like regression where your original question touches on, BIC, AIC, models often, out of domain requirement or not, do watch our model specification. With machine learning mod...
The area under the HOMA-IR curve (AUC) for pre- diabetes/diabetes was 59% (CI: 57–62%), and the best cut-off point based on Youden's index was 2.22 (with 39% sensitivity and 76% specificity); also, the value for HOMA-B was 51% (CI: 49–54%) (Fig. 3) which was not...
4C). In addition, we conducted ROC curve analysis to evaluate the performance of the PAM.score, the AUC was 0.850 for 1-year, 0.831 for 3-year and 0.725 for 5-year (Fig. 4D). We also found the expression of PRMT1, PRMT2, PRMT3, PRMT5, PRMT6, PRMT7, PRMT9 were significantly...