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is it possible to create a multi output random forest regression using a visual analysis ? AFAIK you only can select one feature at a time to be predicted.
I don't know if subpopulation analysis is the way to go here or it must be done via code recipe.
I will reformulate the question 😀.
Having a dataset with the following shape:
- Training X_train : (33873, 17) y y_train :(33873, 15) - Validation_1 X_test : (14517, 17) y y_test : (14517, 15) - Validation_2 X_test2 : (145973, 17) y y_test2 : (145973, 15)
So, let's going to predict 15 values using random forest regressor. is it possible to do that using visual analysis ?
You are correct, it is not possible to build a multi output model using a visual analysis. You can however create a custom model.
To do this in DSS:
Multi Output RF Model (may be helpful?):