Plot the ROC curve of the biomarker model created using a user-selected subset of features. Pred and auroc are lists containing predictions and labels from different cross-validations.
PlotROCTest(mSetObj=NA, imgName, format="png", dpi=72, mdl.inx, avg.method, show.conf, show.holdout, focus="fpr", cutoff = 1.0)Input the name of the created mSetObj (see InitDataObjects)
Input a name for the plot
Select the image format, "png", of "pdf".
Input the dpi. If the image format is "pdf", users need not define the dpi. For "png" images, the default dpi is 72. It is suggested that for high-resolution images, select a dpi of 300.
Model index, 0 means to compare all models, input 1-6 to plot a ROC curve for one of the top six models
Input the method to compute the average ROC curve, either "threshold", "vertical" or "horizontal"
Logical, if 1, show confidence interval, if 0 do not show
Logical, if 1, show the ROC curve for hold-out validation, if 0 do not show
"fpr"
Input the threshold to limit the calculation of the ROC curve, the number must be between 0 and 1.