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Interpretation of labeled data after cross-validation
I am having trouble interpreting the exported labeled data of the cross-validation operator. Nested inside it are either a regression model or a neural net model (we are trying to compare performance).
However, using this method (through the 3rd output port of the cross-validation, test), there is an output of the actual and the predicted value for all rows in the dataset.
Are these predictions being iteratively generated during the folds (and thus each based on a different model) or are they the result of the best performing model being ran on the entire set?
I hope you can clarify this, and also that is has not been answered many times already. Did perform a search but could not find this in the forums.
Thanks a lot in advance.