Extracting predictive results for each loop in a K-fold cross validation or getting the standard deviation for each fold

Dear all

I’ve submitted an article where a reviewer is asking for standard deviation for all scores given (that is: accuracy, f1, cohen’s kappa and AUC) but I have no idea how to provide this with the knime analytics framework.
Ideally I would be able to calculate them in KNIME but I can also extract predictive scores all over and run them on a pyhton script. How would I in that case do that?

Did anyone find a solution for such a request?
I’m running the workflow in a classic loop with a 5-fold cross validation

Best, Chris

have you already tried saving metrics within the cv loop and store/append them in variables / tables “before” the cv loop closes (Nodes like scorer or ROC Cuve,… should be able to return results)

GBT.knwf (26.3 KB)

Dear Daniel.

Please find attached my workflow

I’ve tried with several notes and I just can’t get it to function. Have you done it before?

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