In SAS^® Visual Data Mining and Machine Learning, gradient-boosting models might produce incorrect scores.  As a result, the fit statistics are also incorrect.

The problem occurs in either of these scenarios.

 You run PROC GRADBOOST and all of these conditions are met.

• You have an interval target.
• You specify the OFFSET= option.
• You specify DISTRIBUTION=POISSON or DISTRIBUTION= TWEEDIE.

 You run the Gradient Boosting node in Model Studio and all of these conditions are met.

• You have an interval target.
• Your Interval target distribution property is set to Tweedie or Poisson.
• The Role is set to Offset for one of your variables.

There are no errors or warnings to indicate a problem.

Click the Hot Fix tab in this note for a link to instructions about accessing and applying the software update.

Operating System and Release Information

Viya on Windows: An update for this issue is available for SAS Viya 3.5. For instructions on how to access and apply software updates, see the Updating Your SAS Viya software section in the SAS Viya 3.5 for Windows Deployment Guide at

Viya on Linux: An update for this issue is available for SAS Viya 3.5. For instructions on how to access and apply software updates, see the Updating Your SAS Viya software section in the SAS Viya 3.5 for Linux Deployment Guide at