Example: OOB Errors for Random Forests
OOB Errors for Random Forests
The RandomForestClassifier
is trained using bootstrap aggregation, where each new tree is fit from a bootstrap sample of the training observations . The out-of-bag (OOB) error is the average error for each calculated using predictions from the trees that do not contain in their respective bootstrap sample. This allows the <