What is the impurity criterion and minimum impurity required in Tree Ensemble (Regression) node in KNIME

Hi All,

I am using Tree Ensemble (Regression) node for my modelling exercise. I am interested to know what’s the impurity criterion used to measure the quality of split and minimum value required for the criteria (Something similar is given by Python’s RandomForestRegressor function)
I was not able to find any reference for the criterion in the documentation too. It would be great if anyone could help me with that


Hi @Anushka,

for the Tree Ensemble Regression Learner the “impurity criterion” is mean squared error. Definitely something to be improved in the documentation, thanks for pointing that out.


With version 4.3.4 the node description has been adjusted and now provides additional information on the impurity criterion.


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