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Linear regression cannot handle polynomial label

zainzain Member Posts: 9 Learner I
edited December 2018 in Help
I am new to rapid miner studio and trying to understand the telco customer churn process which is available in the community real-world use cases. But there seems to be an error in the process model I have attached the snapshot of error. Any idea how I can solve this, please?

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Answers

  • zainzain Member Posts: 9 Learner I
    Thank you for the help
  • Telcontar120Telcontar120 Moderator, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,267   Unicorn
    Nominal to Numerical is usually suitable for input attributes but not necessarily for the label.  If you have 4 possible nominal values, you cannot use Nominal to Numerical to reformulate them in a way that would make it a problem suitably solved by the Linear Regression learner.  Fundamentally, linear regression is about predicting a continuous numerical outcome, like "Sales" or "Height" or something similar.  If you have a nominal label, you should look at other learners that are better suited to classification outcomes.
    Note: it is true, if you have two nominal classes, you can "fool" a linear regression into working by recoding it as a dummy (0/1) outcome, but even then you would be better off using logistic regression than pure linear regression.
    Brian T.
    Lindon Ventures 
    Data Science Consulting from Certified RapidMiner Experts
    rfuentealba
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