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I am doing K-fold cross validation and I want to plot an averaged ROC curve in MATLAB. However currently I can only plot K ROC curves in one plot but without knowing the algorithm of averaged ROC curve.

Say I have K lists of $\hat{p}$ and Y(only 0 or 1), or correspondingly I have K lists of FPR and TPR. What should be averaged? Thanks.

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You should not average your k results. Instead, think of cross validation as a way to predict every instance exactly once (no overlapping test sets).

Save your predicted probabilities of each iteration, then plot one ROC curve for your k-fold CV.

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  • $\begingroup$ I got your point. Actually I want "cross-validated ROC" but I might confound it with "mean ROC", so your answer is exactly what I want. By the way, the $\hat{p}$ of all instances come from K models (although they share same algorithm), is it valid enough to simply combine them in one plot? $\endgroup$
    – CuteCat
    Commented Oct 25, 2019 at 15:19
  • $\begingroup$ Yes, that is not only valid, but also preferred. $\endgroup$ Commented Oct 25, 2019 at 22:25

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