I'm new to Knime and I'm having some trouble to get denormalized values of both Regression Predictor and MultiLayerPerceptron Predictor.
First I put the whole dataset through the normalizer node, then I partitioned it into training and validation sets. After obtaining the linear and NN models, I send them to Regression Predictor and MultiLayerPerceptron Predictor, along with the validation data set. Both predictor results are sent to denormalizer nodes. The problem is that when I look into the denormalizer outputs, the predicted values are still normalized. Looks like I should provide the denormalization info of the new predicted variables in order to get it done, but I can't figure how and could't find any examples compatible to 3.4.1 version. I'll be grateful for any help.