I have this simple workflow:
XLS reader -----> Normalizer -----> RProp MLP Learner
XLS reader and Normalizer run OK but when I connect the MLP node, it gets the following:
ARN RProp MLP Learner Input data not normalized. Please consider using the Normalizer Node first.
I had used the normalizer first!
WARN RProp MLP Learner Domain range for regression in column RESPIRAT not in range [0,1]
I didn't use a regression, but a MLP. What does this mean and how can I resolve it?
Thanks in advance,
Did you select all columns for normalization that you later use in the RProp node? Can you please also check the output data on the Normalizer node, if it is in the [0,1] range; right-click the node and select the second last item of the context menu. In the DataTableSpec tab, the lower and upper bounds' values should be 0 and 1. If not, can you please check the settings of the Normalizer and post them here. Thanks.
Did you select all columns for normalization that you later use in the RProp node?
Can you please also check the output data on the Normalizer node, if it is in the [0,1] range;
The values were out of that range. I had used tha z-score normalization. I changed to the Min-Max with the range 0.0 to 1.0 and it's fine now.
Must I connect this node to the Normalizer (apply)? Is it mandatory?
Hi Marta, The Normalizer Apply node can optionally be connected to the second out-port of the Normalizer when you want to normalize a second (test) dataset with the same normalization method. The advantage is that you don't need to readjust the normalization method in both nodes. Regards, Thomas
After I applied the MLP learner I generated PMML code with the PMML writer node.
Later, I used the PMML reader with the generated code and applied a MLP predictor and I get this:
ERROR MultiLayerPerceptron Predictor Execute failed: org.knime.core.data.def.StringCell cannot be cast to org.knime.core.data.DoubleValue
What might be the problem?
I am new at KNIME and I am trying to use it to predict the market price of lands used as warrants in credit operations. That said, I have a data set with the respective lands and their attributes as numbers. Since my output is not nominal, I will have to use a regression, and Neural Networks are great for that purpose. However, I have never used the Rprop model before. Do I have to use a X-Partitioner and X-Aggregator? Since I have to normalize by set before applying the model, how can I denormalize it (only one column)? Thanks in advance!
All the best, Pedro
did you solve the problem?
I have exactly the same issue :(
Thank you in advance
Which of the issues are you referring to? Maybe I can help you with that.