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RSNNS: Neural Networks using the Stuttgart Neural Network Simulator(SNNS)

The Stuttgart Neural Network Simulator (SNNS) is a library containing many standard implementations of neural networks. This package wraps the SNNS functionality to make it available from within R. Using the 'RSNNS' low-level interface, all of the algorithmic functionality and flexibility of SNNS can be accessed. Furthermore, the package contains a convenient high-level interface, so that the most common neural network topologies and learning algorithms integrate seamlessly into R.

Version:0.4-17
Depends:R (≥ 2.10.0), methods,Rcpp (≥ 0.8.5)
LinkingTo:Rcpp
Suggests:scatterplot3d,NeuralNetTools
Published:2023-11-30
DOI:10.32614/CRAN.package.RSNNS
Author:Christoph Bergmeir [aut, cre, cph], José M. Benítez [ths], Andreas Zell [ctb] (Part of original SNNS development team), Niels Mache [ctb] (Part of original SNNS development team), Günter Mamier [ctb] (Part of original SNNS development team), Michael Vogt [ctb] (Part of original SNNS development team), Sven Döring [ctb] (Part of original SNNS development team), Ralf Hübner [ctb] (Part of original SNNS development team), Kai-Uwe Herrmann [ctb] (Part of original SNNS development team), Tobias Soyez [ctb] (Part of original SNNS development team), Michael Schmalzl [ctb] (Part of original SNNS development team), Tilman Sommer [ctb] (Part of original SNNS development team), Artemis Hatzigeorgiou [ctb] (Part of original SNNS development team), Dietmar Posselt [ctb] (Part of original SNNS development team), Tobias Schreiner [ctb] (Part of original SNNS development team), Bernward Kett [ctb] (Part of original SNNS development team), Martin Reczko [ctb] (Part of original SNNS external contributors), Martin Riedmiller [ctb] (Part of original SNNS external contributors), Mark Seemann [ctb] (Part of original SNNS external contributors), Marcus Ritt [ctb] (Part of original SNNS external contributors), Jamie DeCoster [ctb] (Part of original SNNS external contributors), Jochen Biedermann [ctb] (Part of original SNNS external contributors), Joachim Danz [ctb] (Part of original SNNS development team), Christian Wehrfritz [ctb] (Part of original SNNS development team), Patrick Kursawe [ctb] (Contributors to SNNS Version 4.3), Andre El-Ama [ctb] (Contributors to SNNS Version 4.3)
Maintainer:Christoph Bergmeir <c.bergmeir at decsai.ugr.es>
MailingList:rsnns@googlegroups.com
BugReports:https://github.com/cbergmeir/RSNNS/issues
License:LGPL-2 |LGPL-2.1 |LGPL-3 | fileLICENSE [expanded from: LGPL (≥ 2) | file LICENSE]
Copyright:Original SNNS software Copyright (C) 1990-1995 SNNS Group,IPVR, Univ. Stuttgart, FRG; 1996-1998 SNNS Group, WSI, Univ.Tuebingen, FRG. R interface Copyright (C) DiCITS Lab, Sci2sgroup, DECSAI, University of Granada.
URL:https://github.com/cbergmeir/RSNNS
NeedsCompilation:yes
Citation:RSNNS citation info
Materials:ChangeLog
In views:MachineLearning
CRAN checks:RSNNS results

Documentation:

Reference manual:RSNNS.html ,RSNNS.pdf

Downloads:

Package source: RSNNS_0.4-17.tar.gz
Windows binaries: r-devel:RSNNS_0.4-17.zip, r-release:RSNNS_0.4-17.zip, r-oldrel:RSNNS_0.4-17.zip
macOS binaries: r-release (arm64):RSNNS_0.4-17.tgz, r-oldrel (arm64):RSNNS_0.4-17.tgz, r-release (x86_64):RSNNS_0.4-17.tgz, r-oldrel (x86_64):RSNNS_0.4-17.tgz
Old sources: RSNNS archive

Reverse dependencies:

Reverse imports:DaMiRseq,E2E,FRI,noisemodel,semiArtificial,TSPred
Reverse suggests:FSinR,mistyR,mlr,NeuralNetTools,NeuralSens
Reverse enhances:vip

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=RSNNSto link to this page.

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