neuralnet: Training of Neural Networks

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.

Version:	1.44.2
Depends:	R (≥ 2.9.0)
Imports:	grid, MASS, grDevices, stats, utils, Deriv
Suggests:	testthat
Published:	2019-02-07
DOI:	10.32614/CRAN.package.neuralnet
Author:	Stefan Fritsch [aut], Frauke Guenther [aut], Marvin N. Wright [aut, cre], Marc Suling [ctb], Sebastian M. Mueller [ctb]
Maintainer:	Marvin N. Wright <wright at leibniz-bips.de>
BugReports:	https://github.com/bips-hb/neuralnet/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://github.com/bips-hb/neuralnet
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	neuralnet results

Documentation:

Reference manual:

neuralnet.html , neuralnet.pdf

Downloads:

Package source:	neuralnet_1.44.2.tar.gz
Windows binaries:	r-devel: neuralnet_1.44.2.zip, r-release: neuralnet_1.44.2.zip, r-oldrel: neuralnet_1.44.2.zip
macOS binaries:	r-release (arm64): neuralnet_1.44.2.tgz, r-oldrel (arm64): neuralnet_1.44.2.tgz, r-release (x86_64): neuralnet_1.44.2.tgz, r-oldrel (x86_64): neuralnet_1.44.2.tgz
Old sources:	neuralnet archive

Reverse dependencies:

Reverse depends:	MARSANNhybrid, quarrint
Reverse imports:	AriGaMyANNSVR, CEEMDANML, ConvertPar, DeepLearningCausal, FRI, FWRGB, Imneuron, ImNN, LilRhino, Modeler, nnfor, reddPrec, RSDA, SignacX, trackdem, traineR, WaveletML, WaveST
Reverse suggests:	gemR, innsight, mcboost, misspi, mlr, NeuralNetTools, NeuralSens, plotmo, qeML, TrafficBDE
Reverse enhances:	vip

Linking:

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