# Cross-Validation

```{r setup, include = FALSE}
knitr::opts_chunk$set(echo = TRUE, fig.align = "center", cache = TRUE, autodep = TRUE)
```

This chapter will introduce no new modeling techniques, but instead will focus on evaluating models through the use of **cross-validation.**

Specifically, we will discuss:

- How to "manually" perform **cross-validation** for any model-metric combination.
- The need for **cross-validation**.
- The need for a separate **test set** outside of the **training data** where cross-validation takes place.

This chapter is currently **under construction**. While it is being developed, the following links to the STAT 432 course notes.

- [**Notes:** Simulation](files/simulation.pdf)
- [**Notes:** Bootstrap](files/bootstrap.pdf)
- [**Notes:** Cross-Validation](files/cross-validation.pdf)
