Hi, I have rapidminer deep learning predictive model for a output variable, I want to see how to the model performs to a different outcome variable using the same learning information. What would be the best operator to use ? Thanks
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Answers
sgenzerAdministrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM ModeratorPosts: 2,959 Community Manager
hi @aksaha I'm not sure exactly what you mean here. Do you want to rebuild the model with a new predicted class, or do you want to score the model on new data with the same predicted class? The latter is easy - just use Apply Model. The former is not hard either - just use Set Role to set a new predicted class and build the model again.
If you are looking to predict multiple label columns, which I think you are trying to do. You need to use a "Multi-label modeling" operator. You can see the tutorial in that operator "help" window.
Note: Multi-label modeling creates multiple models based on the number of outcome variables (attributes) you are trying to predict.
I want to see how to the model performs to a different outcome variable using the same learning information
Generally, a model trained for one outcome variable will support prediction for that variable. If you are looking for "transfer learning" then I am not sure if rapidminer supports that.
If you are trying to predict the same label column for new data, then @sgenzer suggestion works
Answers
Does that help?
Scott
If you are looking to predict multiple label columns, which I think you are trying to do. You need to use a "Multi-label modeling" operator. You can see the tutorial in that operator "help" window.
Note: Multi-label modeling creates multiple models based on the number of outcome variables (attributes) you are trying to predict.
If you are trying to predict the same label column for new data, then @sgenzer suggestion works
Varun
https://www.varunmandalapu.com/
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