Training a neural network with nnet
The nnet package is another package that can deal with artificial neural networks. This package provides the functionality to train feed-forward neural networks with traditional backpropagation. As you can find most of the neural network function implemented in the neuralnet package, in this recipe we provide a short overview of how to train neural networks with nnet.
Getting ready
In this recipe, we do not use the trainset and trainset generated from the previous step; please reload the iris dataset again.
How to do it...
Perform the following steps to train the neural network with nnet:
- First, install and load the
nnetpackage:
> install.packages("nnet")> library(nnet)
- Next, split the dataset into training and testing datasets:
> data(iris)
> set.seed(2)
> ind = sample(2, nrow(iris), replace = TRUE,
prob=c(0.7, 0.3))
> trainset = iris[ind == 1,]
> testset = iris[ind == 2,]- Then, train the neural network with
nnet...
