Why am I getting a 1.000 ROC area value even when

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.