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: 1.33
Depends: R (≥ 2.9.0)
Imports: grid, MASS, grDevices, stats, utils
Published: 2016-08-16
Author: Stefan Fritsch [aut], Frauke Guenther [aut, cre], Marc Suling [ctb], Sebastian M. Mueller [ctb]
Maintainer: Frauke Guenther <guenther at leibniz-bips.de>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: neuralnet results

Downloads:

Reference manual: neuralnet.pdf
Package source: neuralnet_1.33.tar.gz
Windows binaries: r-devel: neuralnet_1.33.zip, r-release: neuralnet_1.33.zip, r-oldrel: neuralnet_1.33.zip
OS X binaries: r-release: neuralnet_1.33.tgz, r-oldrel: neuralnet_1.33.tgz
Old sources: neuralnet archive

Reverse dependencies:

Reverse depends: quarrint
Reverse imports: Modeler, nnfor, RTransProb, spartan, trackdem, TrafficBDE
Reverse suggests: fscaret, mlr, NeuralNetTools, nnetpredint, plotmo

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