Machine Learning with R Cookbook - Second Edition

How it works...

In this recipe, we demonstrate steps to train a neural network model with the nnet package. We first use nnet to train the neural network. With this function, we can set the classification formula, the source of data, the number of hidden units in the size parameter, the initial random weight in the rang parameter, the parameter for weight decay in the decay parameter, and the maximum iteration in the maxit parameter. As we set maxit to 200, the training process repeatedly runs till the value of the fitting criterion plus the decay term converge. Finally, we use the summary function to obtain information about the built neural network, which reveals that the model is built with 4-2-3 networks with 19 weights. Also, the model ...