Neural Networks with R

Neural network model

As we did in the previous example, before building and training the network, we have to run the standardization of data. In this case, we will adopt min-max standardization.

Remember, it is good practice to normalize the data before training a neural network. With normalization, data units are eliminated, allowing you to easily compare data from different locations.

Before we begin, make a further check by using the str() function. This function provides a compact display of the internal structure of an object, a diagnostic function, and an alternative to the summary() function. Ideally, only one line for each basic structure is displayed. It is especially well suited to compactly display the (abbreviated) contents of ...