ROC curves for the automatically generated classifier codes

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Aalaas
Aalaas 2016-11-22
Hi everyone,
I've generated some code for several classiffiers using the Classiffication Learner app. These codes only give the accuracy to validate the classifiers, but they don't give any ROC curve values. I want to add some code to compute the AUC of the ROC curves, but I'm a bit confused.
I'm using the perfcurve function, so I have to give it the actual values of the labels and the classification scores. I do have the values of the labels, but for the scores, I have a reduced set of values as the classifier is being "partitioned" in K folds.
Can someone guide me on how should I compute the ROC values in this case?
Thank you!!

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