Test model for different outcome variable

User: "aksaha"
aksaha
New Altair Community Member
Updated by Jocelyn
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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    User: "sgenzer"
    sgenzer
    Altair Employee
    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.

    Does that help?

    Scott
    User: "varunm1"
    varunm1
    New Altair Community Member
    Hello @aksaha

    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 
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