I used 10 fold cross-validation to partition the data. When I tried to compare the model performance, I used PMML to cell which is connected to learner node, however I encountered an error “cannot continue the loop as the workflow was executed while loop being partially executed”. If I use partitioning node then it is fine. My question is: can you use the PMML to cell node if you do cross-validation?
Thanks!
Hi there!
Which node reports error? How did you mean to compare models? Can you maybe post a screenshot of a workflow for better understanding of connections?
Here is a workflow example where different models are trained and evaluated with cross validation and the best is chosen. Hope it will help.
Br,
Ivan
Ivan,
Thank you. That workflow is helpful. I was trying to replicate this workflow by using cross validation rather than partitioning node. I think that would not be feasible.
I do have a question on the credit scoring workflow you posted. When it writes out the best model, it should be the model that was obtained using cross-validation right? So if I want to deploy the best model, I need to run it on the entire dataset and then get the model that I can use for possible new data. Is that correct?
Hi @Learn2019!
Glad you find it helpful. On KNIME Hub you can search for nodes, workflows and in future much more 
Haven’t checked in details but don’t see why wouldn’t it be feasible to use cross validation on workflow from picture.
No. Cross-validation is used for validating model and that is why in Credit scoring workflow you use Scorer node after cross-validation. Bottom branch is for model you will deploy - if it is the best at the end of course.
Here is another simpler workflow for cross-validation and corresponding topic from forum that can help.
If you will have any more questions don’t hesitate 
Br,
Ivan
Thank you very much!
