9.6 Resampling methods (5): Leave-one-out cross-validation (LOOCV)

\[CV_{(n)} = \frac{1}{n}\sum_{i=1}^{n}Err_{i}\] where \(Err_{i}=I(y_{i}\neq\hat{y}_{i})\), i.e., is 1 when \(y_{i}\) was wrongly predicted

  • Linear regression: Use MSE rather than number of misclassified observations to quantify test error

  • The k-fold CV error rate (see next slide) and validation set error rates are defined analogously


James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2013. An Introduction to Statistical Learning: With Applications in R. Springer Texts in Statistics. Springer.