R Programming By Example

Training our first predictive model

Following best practices, we will use Cross Validation (CV) as the basis of our modeling process. Using CV we can create estimates of how well our model will do with unseen data. CV is powerful, but the downside is that it requires more processing and therefore more time. If you can take the computational complexity, you should definitely take advantage of it in your projects.

Going into the mathematics behind CV is outside of the scope of this book. If interested, you can find out more information on Wikipedia (https://en.wikipedia.org/wiki/Cross-validation_(statistics)). The basic idea is that the training data will be split into various parts, and each of these parts will be taken out of the rest of ...