This chapter shows how to build and train basic neural networks in R through hands-on examples that also emphasize the importance of evaluating different tuning parameters for models to find the best set. Although evaluating a variety of tuning parameters can help increase the performance of a model, it can also lead to overfitting, the next topic covered in the chapter. The chapter closes with an example use case classifying activity data from a smartphone as walking, going up or down stairs, sitting, standing, or lying down.
This chapter covers the following topics:
Neural networks in R
The problem of overfitting data – the consequences explained
Use case – build and apply a neural network