2 weeks ago
I was reading this Book - Customer Segmentation and Clustering Using SAS Enterprise Miner (3rd Edition) - and noticed the author does a demonstration where he classifies the variable CHANNEL (with 4 distinct and discrete levels) as continuous instead of nominal.
I have never thought of it, but does anyone know what the consequences of this will if the variable CHANNEL was misclassified and fed into a predictive model?
2 weeks ago - last edited 2 weeks ago
First of all, if this variable is not ordinal, it will be treated as actually having an order, and essentially you are fitting a linear model through the 4 levels, and I don't see any sense to that. I can't really guess how that would affect a predictive model, other than to say it's simple and easy to handle the variable properly (as nominal), and thus I would not recommend handling it as continuous. In fact, if I was a reviewer for a journal and someone turned a nominal (not ordinal) variable into continuous, I'd probably reject the paper.