ine `\(y\)` outcome and `\(x\)` predictor variables  
2. Remove `\(y\)` variable from `\(x\)` predictor datasets  
3. Handle missing data (if present)  
4. Scale data (if necessary)  
5. Convert factors to indicators (if necessary)  
6. Define training and test datasets  

### Open "2-preprocessing.Rmd" to get started with the data.  

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# Cross-validation

[Cross-validation](https://en.wikipedia.org/wiki/Cross-validation_(statistics%29) is a way to measure model performance of an entire dataset by repea