问题
I am using Weka as a classifier, and it has worked great for me so far. However, in my last test, I got a 1.000 ROC area value (which, if i remember correctly, represents a perfect classification) without having 100% of accuracy, as can be seen in the Confusion Matrix in the Figure.
My question is: Am I interpreting the results incorrectly or am I getting wrong results (maybe the classifier I am using is badly programmed, although I don't think it's likely)?
Classification output
Thank You!
回答1:
The accuracy is measured at one specific threshold, typically 0.5. If the AUC is 1, it means that you have an other threshold with perfect classification, in your case I would guess a lower one.
来源：https://stackoverflow.com/questions/39145083/why-am-i-getting-a-1-000-roc-area-value-even-when-i-dont-have-100-of-accuracy