How to generate a ROC curve for a cross validation?
For a single test I think I should threshold the classification scores of SVM to generate the ROC curve.
But I am unclear about how to generate it for a cross validation?
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As follow-up to Backlin:
The variation in the results for different runs of k-fold or leave-n-out cross validation show instability of the models. This is valuable information.
see e.g. the R package ROCR
Here’s an example: the shaded areas are the inter quartile ranges observed over 125 iterations of 8-fold cross validation. The thin black areas contain half of the observed specificity-sensitivity pairs for one particular threshold, median marked by x (ignore the + marks).