In SAS Model Studio, a data scientist selects the 'Gradient Boosting' node and wants to tune the number of trees using AutoTune. Which SAS Viya feature enables automatic hyperparameter search for gradient boosting?
Select an answer to reveal the explanation.
Short Explanation
Here's the deal — the AutoTune node in SAS Model Studio is what you use to automatically search hyperparameters for gradient boosting. It can use Bayesian optimization or random/grid search to tune settings like number of trees, learning rate, and max depth.
Full Explanation
The correct approach is SAS Model Studio's AutoTune node, also called hyperparameter optimization, because it automatically searches the hyperparameter space using strategies such as Bayesian optimization, random search, or grid search, and it can optimize gradient boosting parameters such as learning rate, number of trees, and max depth. The PROC HPFOREST with AUTOTUNE=YES option is wrong because PROC HPFOREST does not have an AUTOTUNE=YES option. The gbtreetrain CAS action with GRIDSEARCH=YES parameter is wrong because gbtreetrain does not have a GRIDSEARCH=YES parameter. The PROC GLMSELECT with SELECTION=AUTOTUNE option is wrong because PROC GLMSELECT is for variable selection in linear models, not gradient boosting hyperparameter search.