How does PROC HPFOREST handle missing values in predictor variables during training and scoring?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because PROC HPFOREST uses surrogate splits — when the primary split variable is missing, it uses the best surrogate variable (most correlated with the primary split) to route the observation. A is wrong; missing observations are not excluded.
Full explanation below image
Full Explanation
B is correct because PROC HPFOREST uses surrogate splits — when the primary split variable is missing, it uses the best surrogate variable (most correlated with the primary split) to route the observation. A is wrong; missing observations are not excluded. C and D describe imputation strategies that PROC HPFOREST does not apply; it handles missing values natively via surrogate splits.