# Logistic regression says only one label

I'm having a hard time finding a work around with this problem. So, I used Discretize by User Specification to categorized the values into five categories (Above Average, MTM, AM, LM, and VLM) then I set its role to label. I then used Cross Validation. This is where I started encountering problems, in the training area I used a logistic regression model but apparently it cannot handle a polynomial label. After browsing the internet, I used the Polynominal by Binominal Classification model then put the Logistic Regression model there. The error was gone but when I ran the process it says that it does have sufficient capabilities in handling an example set with only one label.

Correct me if I'm wrong, as I know, Logistic regression will run as long there are two values in a label (for example like yes or no). But why is it saying that my label has only one value when in fact it has five.

Correct me if I'm wrong, as I know, Logistic regression will run as long there are two values in a label (for example like yes or no). But why is it saying that my label has only one value when in fact it has five.

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## Answers

1,195UnicornI think that due to "bad luck", one of your folds during the

Cross Validationcontains only examples with one value of your labelMaybe have you got an imbalanced dataset too ?

Try to use

Split ValidationinsteadCross Validationand tell us if this error is still present...Regards,

Lionel

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