If you were using a binary target, I would have suggested you look at Usage Note 47965 which describes some approaches to modeling a rare target level (http://support.sas.com/kb/47/965.html) which is often the reason why a default Tree or Gradient Boosting model does not find any splits. Since the target is interval, consider using some of the following approaches to identifying possible issues:
1 - Review the log - sometimes the log explains why splits were not found for certain variables
2 - Run a Variable Selection node to identify which if any of the variables appear to be useful for splitting
NOTE: The Variable Selection node generates grouped versions of the nominal/ordinal variables, and it optionally can create grouped versions of interval variables.
3 - Evaluate the distribution/relationship between the target variable and the grouped and ungrouped versions of the variables identified as important to determine if there are any potential concerns (e.g. is the target heavily skewed? are there too many missing values in the input? are there too many class levels for a nominal variable? is there too little support for the target in large ranges of the interval variable? etc...)
4 - Run a Decision Tree against the data to see if it generates any splits, and review the results to see if there are any apparent issues that might point to a cause.
5 - Create a binary target out of your interval target by creating a threshold (e.g. flag those observations that are in the top 10% of the data) as "Yes" and the rest as "No". You can then try the approaches given in Usage Note 47965 for a binary target.
Hope this helps!
Cordially,
Doug
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