How to use logistic regression for multi-class classification in rapidminer?

Logistic regression only works with binominal (2-class) labels.  However, the Generalized Linear Model operator has a multinomial regression solver which is suitable for 3-class labels (or more). 
There is a sample process for it available in the operator help that should guide you.
There are also many other ML operators that can handle multinomial labels.

Hello @Telcontar120

Is the solution suggested in your post similar to the multinomial logistic regression in python? I generally use python for this. I feel they might be similar but just want your insight.

Also, we can try polynomial to binomial (One Vs All) and apply logistic regression on that directly.

@varunm1 this is more of a question for @mschmitz but as far as I know, the multinomial GLM in RapidMiner would be very similar to the multinomial LR python function.
The one-vs-all-other method is a workaround but isn't suitable if you really do want simultaneous predictions for multiple classes.

Thanks Brian.