Feature Importance for Regression Random Forest
Hello Everyone,
I am looking for an operator (or any other way) to find the attribute importance of my model.
I have selected an RF model and tried to use the operator "Weight by Tree Importance" to find the weights of my attributes. However, I received the following error message:
Attribute Weights cannot be extracted from regression trees.
My dataset contains numerical and nominal attributes, and the label is numerical (double).
I am looking for an operator (or any other way) to find the attribute importance of my model.
I have selected an RF model and tried to use the operator "Weight by Tree Importance" to find the weights of my attributes. However, I received the following error message:
Attribute Weights cannot be extracted from regression trees.
My dataset contains numerical and nominal attributes, and the label is numerical (double).
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Altair EmployeeIt is also worth noting that the random forest operator already produces a weights object which gives you information on the importance of different variables. The extension I mention above just adds more granularity and is appropriate to most models.
I would recommend having a look at the interpretations extension, see: https://community.rapidminer.com/discussion/58471/new-extension-interpretations-shap-lime-and-shapely
Please let me know how you get on.
Best,
Roland