When I run the gradient boosting model in SAS enterprise miner, it only does one iteration even though I specified 100 iterations. None of the variables turn out to be important. The root mean square error for both validation and training was a vertical line at the exact same point(overlapping each other). I get this weird result when I use 40% or more observations as training. When I use a smaller percentage of observation as my training set, I don't have this issue. I have tried other modelling techniques and get regular results irrespective of varying training/validation sample sizes. My dataset has about 400,000 observations. Any thoughts? Suggestions? |
A similar situation was recently resolved by specifying LEAFFRACTION to small number, such as 0.001.
Yes this is weird. I guess no split is created in the initial tree. I cannot guess why reducing the number of training observations fixes it. If you are willing and able to provide the data to SAS Tech Support, I will figure out why this is happening.
-Padraic
A similar situation was recently resolved by specifying LEAFFRACTION to small number, such as 0.001.
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