Intepreting random forest model output


I am a relatively new user to KNIME, and I built a random forest predictor (regression) model in KNIME where my predictor (or independent) variable is binary (1,0) and my outcome (i.e. dependent) variable is ordinal with values 0 to 10. For my binary variable, “1” means it is present, and “0” means it is absent. I want to know what the predicted outcome would be from the random forest model if my predictor variable is a 1 i.e. present. In the “prediction Output” table, should I only look at the predicted values that correspond to a “1” in my predictor variable?

Thank you in advance

You could use new data and predict to see. It looks like you have a multilabel classification task. Why then using a regression?

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