October 2017
Beginner to intermediate
572 pages
26h 1m
English
The neural network is constructed with an interconnected group of nodes, which involves the input, connected weights, processing element, and output. Neural networks can be applied to many areas, such as classification, clustering, and prediction. To train a neural network in R, you can use neuralnet, which is built to train multilayer perception in the context of regression analysis and contains many flexible functions to train forward neural networks. In this recipe, we will introduce how to use neuralnet to train a neural network.
Read now
Unlock full access