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Optimization Grid with Random Forest - Not Working.
RapidMiner Unicorns 🦄,
I trying to run a optimization grid with our my Random Forest model and I am getting an error. It's stating that gain_ratio criterion cannot be used for numeric labels (see pictures below). I checked all my parameters and I am not using gain_ratio in the optimization grid (see pictures below). So, specifically how you used a optimization grid with cross validation, and random forest predicting a real number in RapidMiner?
Can you send an basic working example of this workflow process with with good documented comments explaining each step.
I trying to run a optimization grid with our my Random Forest model and I am getting an error. It's stating that gain_ratio criterion cannot be used for numeric labels (see pictures below). I checked all my parameters and I am not using gain_ratio in the optimization grid (see pictures below). So, specifically how you used a optimization grid with cross validation, and random forest predicting a real number in RapidMiner?
Can you send an basic working example of this workflow process with with good documented comments explaining each step.
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Answers
Dortmund, Germany
Dortmund, Germany
Specifically what configuration/setup tasks are needed to make the grid optimization operator work and simply find the optimal parameters for Random Forest model? Do you have a sample workflow of how this can work?
Specifically what configuration/setup tasks are needed to make the grid optimization operator work and simply find the optimal parameters for Random Forest model? Do you have a sample workflow of how this can work?
Just select correct and applicable settings for the optimization. Leave the criterion alone (it has to be least_square for numerical prediction) and optimize parameters like the number of trees and the maximum depth.
Regards,
Balázs