Linear regression cannot handle polynomial label
I am new to rapid miner studio and trying to understand the telco customer churn process which is available in the community realworld 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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Best Answer

rfuentealba Moderator, RapidMiner Certified Analyst, Member, University Professor Posts: 566 UnicornHi @zain, and a warm welcome to the community!
A Logistic Regression is, like many (but not all) machine learning models, a mathematical formula. A polynominal field is text, hence not suitable for calculations.
How to solve it? Super easy: there is an operator named Nominal to Numerical. It does something weird with your data (not that weird, but you might want to see it for yourself by adding a breakpoint), transforming it into 0's and 1's, the kind of entry that suits your algorithm. Just put that before your Logistic Regression operator and let's see if it works.
(Notice that linear and logistic regressions, while similar, are not the same. Your model is using logistic regression).
All the best,
Rodrigo.
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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.
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