Tree Ensemble (Regression) Output Interpretation



I am having trouble conducting a Tree Ensemble Regression analysis in the 2.11.3 version of KNIME. I have set up my workflow as Partitioning > Tree Ensemble Learner (Regression) > Tree Ensemble Predictor (Regression) > Scorer (these are the nodes in the workflow. Screenshot attached and alternative link to screenshot: I am struggling mightily to interperet the output tables from any of these nodes following the analysis.


I would like to know 1) what is the model that has been created, i.e. coefficients, etc. and 2) how is the model performing, accuracy of the model using training data and predictor data.


Have I set up the workflow correctly? If I have set it up correctly, am I failing to interperet the output correctly?



For regression models you wouldn't use the "Scorer" node. The scorer is used for classification tasks.

Have a look at the "Numeric Scorer". The node description to that node gives further information, including wiki links on what these measures tell you.

Hope that helps.