Hi all, the functions predefined in the notebook (fit_model and preprocess_X_data) have different arguments for the dependent and independent variables (ie, ydata and Xdata). I am more comfortable working with one data frame that contains all the variables (train_data) for several reasons, but since the submission requires to use those functions I cannot do that. Is there any way to work around this?
Thanks and regards,
Hi @matiasbatto
I understand that this can be a little annoying, specially for R users and some Python packages.
We had to strike a balance that was 1) understood clearly and 2) worked well for many applications, and hence we have this template.
But I think you can work around this easily. One way is through your preprocessing function. For example you could have a preprocessing function with two parameters, where if the second parameter is passed (i.e. the ydata) then it combines them and if not then it does something else.
Would that work for you?
If not then let me know and we will figure out a better solution.
Ok, thanks for the quick reply. I think that will work. I didn’t know I could change the parameters of the preprocessing function.