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

• In classification setting LOOCV error rate takes the form :

$CV_{(n)} = \frac{1}{n}\sum_{i=1}^{n}Err_{i}$ 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

### References

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