neuralnet: Training of Neural Networks
Version 1.33

Training of neural networks using backpropagation, resilient backpropagation with (Riedmiller, 1994) or without weight backtracking (Riedmiller and Braun, 1993) or the modified globally convergent version by Anastasiadis et al. (2005). The package allows flexible settings through custom-choice of error and activation function. Furthermore, the calculation of generalized weights (Intrator O & Intrator N, 1993) is implemented.

AuthorStefan Fritsch [aut], Frauke Guenther [aut, cre], Marc Suling [ctb], Sebastian M. Mueller [ctb]
Date of publication2016-08-16 12:08:44
MaintainerFrauke Guenther <guenther@leibniz-bips.de>
LicenseGPL (>= 2)
Version1.33
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("neuralnet")

Getting started

Package overview

Popular man pages

compute: Computation of a given neural network for given covariate...
confidence.interval: Calculates confidence intervals of the weights
gwplot: Plot method for generalized weights
neuralnet: Training of neural networks
neuralnet-package: Training of Neural Networks
plot.nn: Plot method for neural networks
prediction: Summarizes the output of the neural network, the data and the...
See all...

All man pages Function index File listing

Man pages

compute: Computation of a given neural network for given covariate...
confidence.interval: Calculates confidence intervals of the weights
gwplot: Plot method for generalized weights
neuralnet: Training of neural networks
neuralnet-package: Training of Neural Networks
plot.nn: Plot method for neural networks
prediction: Summarizes the output of the neural network, the data and the...

Functions

backprop Source code
calculate.data.result Source code
calculate.delta Source code
calculate.generalized.weights Source code
calculate.gradients Source code
calculate.information.matrices Source code
calculate.neuralnet Source code
calculate.predictions Source code
compute Man page Source code
compute.net Source code
confidence.interval Man page Source code
differentiate Source code
display Source code
draw.text Source code
generate.initial.variables Source code
generate.output Source code
generate.rownames Source code
generate.startweights Source code
gwplot Man page Source code
minus Source code
neuralnet Man page Source code
neuralnet-package Man page
plot.nn Man page Source code
plus Source code
prediction Man page Source code
print.nn Man page Source code
relist Source code
remove.intercept Source code
rprop Source code
type Source code
varify.variables Source code

Files

NAMESPACE
R
R/compute.r
R/neuralnet.r
R/plot.nn.r
R/confidence.interval.r
R/prediction.r
R/gwplot.r
MD5
DESCRIPTION
man
man/neuralnet.Rd
man/prediction.Rd
man/compute.Rd
man/gwplot.Rd
man/neuralnet-package.Rd
man/plot.nn.Rd
man/confidence.interval.Rd
neuralnet documentation built on May 19, 2017, 10:49 a.m.

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