How scores are calculated with random forests to be used in ROC analysis

Random forests is used in the BIOMARKER ANALYSIS function in the “Tester module”, where we can chose appropriate compounds to be used simultaneously to build a ROC curve. I wonder how scores from the selected compounds can be built to be assessed in the ROC analysis using random forests. I tried to use the mean decrease accuracy as a weighted factor to apply to each compound value, but I did not reproduce the roc curve displayed while using the random forest key. The R commands are not usefull to me with this regard. Thank you for helping

Are you referring to reproducing the ROC in Tester mode vs Explorer mode? If so, you cannot. Explorer ROC and Tester ROC are for different purposes. Explorer ROC is more complex (double CV) in order to select features and to evaluate performance; while Tester just performs conventional CV (single CV) based on the given features. However, they will converge for very large sample (>500), in my experience.

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