Year: 2010
Type: article
Abstract: Artificial neural networks are applied in many situations.neuralnet is built to train multi-layer perceptrons in the context of regression analyses, i.e. to approximate functional relationships between covariates and response variables.Thus, neural networks are used as extensions of generalized linear models.neuralnet is a very flexible package.The backpropagation algorithm and three versions of resilient backpropagation are implemented and it provides a custom-choice of activation and error function.An arbitrary number of covariates and response variables as well as of hidden layers can theoretically be included.The paper gives a brief introduction to multilayer perceptrons and resilient backpropagation and demonstrates the application of neuralnet using the data set infert, which is contained in the R distribution.
Source: The R Journal
DOI: 10.32614/rj-2010-006
Authors: Frauke Günther, Stefan Fritsch
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W94052953