Chapter 07.03: Out-of-Bag Error Estimate

We introduce the concepts of in-bag and out-of-bag observations and explain how to compute the out-of-bag error estimate.

Lecture video

Lecture slides

Quiz

--- shuffle_questions: false --- ## Which statements are true? - [x] The OOB error shares similarities with cross-validation estimation. It can also be used for a quicker model selection. - [x] In random forests for classification, a good rule of thumb is to use mtry = $\sqrt{p}$.