Hi WW, you have a Nominal variable that either needs to be set to Interval or Rejected altogether. For example, if you set Zip Code to Nominal there are too many levels in that field for it to be set to Nominal. You can also transform it using the SAS Code Node so that it has less levels.
I have a few nominal variables as inputs and the main one out of these are set as the "ID" as it is an unique identifier like a referrance number.
Maybe they are the ones that are causing the problem, but if I reject them the model im building wouldnt work.
How do you use the SAS code node to lessen the levels?
If I group these variables in to sub groups would that work?
Also as suggested I would recommend being careful about using a variable like zip code or other nominal variables that have a really large number of discrete nominal values as predictors (inputs). You can reject this variable or using a binning technique.
Hey Wickey, ID variables should not be the cause of this error, only input nominal variables. You can bin the variable using the transform node or write code in a sas code node. For vars like Zip Code you can also truncate the value and use the first two or three digits, as long as the geographic area is regional because national would still cause too many levels.
This is unrelated to your original problem, (although I did learn the hard way and finally figured out the numeric variable errors issue recently myself), & I'm not sure what you are working on, but, would a spatial regression model or something that captures spatial correlation be useful in your work? Not sure how it can be implemented in Miner though, but curious.