A SAS data scientist uses the following code: PROC HPFOREST DATA=train SEED=999; TARGET churn / LEVEL=NOMINAL; INPUT age income tenure / LEVEL=INTERVAL; INPUT segment / LEVEL=NOMINAL; OOB; RUN; What does the OOB statement request?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — a is correct because OOB in PROC HPFOREST requests Out-Of-Bag error estimation. Each tree is trained on a bootstrap sample, and the approximately 37% of observations not selected (the OOB observations) are used to compute an unbiased validation error estimate without needing a separate holdout set.
Full explanation below image
Full Explanation
A is correct because OOB in PROC HPFOREST requests Out-Of-Bag error estimation. Each tree is trained on a bootstrap sample, and the approximately 37% of observations not selected (the OOB observations) are used to compute an unbiased validation error estimate without needing a separate holdout set. B, C, and D are fabricated interpretations with no basis in SAS documentation.