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How to generate a ROC curve for a dataset?

I would like to generate a ROC curve for my dataset containing two classes(A,B) The data-set has around 16000 columns and 60 rows. And the last column Class represents the class of the variables.

Now do I need to iterate the whole code 10 times(since i m doing 10 cross validation) to generate 10 different confusion matrix, and based on that I can draw ROC curve on to check the performance of training and test data??

r roc machine-learning svm

1 answer

You can generate 10 ROC curves with 10 AUC scores. AUC scores can be compared easily.

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