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564.
Out-of-Bag Error Estimation
medium
Out-of-bag (OOB) error is a built-in validation mechanism in Random Forests. How is it computed?
A
OOB error is computed by averaging the training errors of all trees on their own bootstrap samples
B
Each sample is randomly assigned to a validation fold and evaluated by all trees trained on other folds
C
Each training sample is evaluated only by trees for which it was not included in the bootstrap sample
D
Each tree is evaluated on a held-out validation set that is randomly sampled before training begins
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