Loop over pairs of attributes
Hi,
I have a dataset containing two sets of generally named attributes: (label_1,..., label_91) (pd_1,...,pd_91)
I would like to create a loop process inside which there will be a linear regression, with the label attribute being the respective looped label_ and the regression is using the previous day data for building the model (pd_ attribute)
So I want to loop pairs of attributes: label_1 and pd_1; label_2 and pd_2; label_3 and pd_3 etc.
So that only the correct previous day data for the label attribute is used in each linear regression.
I cannot seem to find any solution, as the Loop Attributes only loops one attribute (e.g. the label_ here)
Nesting Loop Attributes would result in looping over all pd_ attributes for one label_, which is not needed as I only need one selected pd_ for each label_
Loop Attribute Subsets have the same problem, I don't need to have all combinations, only the selected ones
Could you suggest any solution?
Thank you very much for your help in advance!