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: 0.4-10
Depends: R (≥ 2.10.0), methods, Rcpp (≥ 0.8.5)
LinkingTo: Rcpp
Suggests: scatterplot3d, NeuralNetTools
Published: 2017-12-10
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>
BugReports: https://github.com/cbergmeir/RSNNS/issues
License: LGPL-2 | LGPL-2.1 | LGPL-3 | file LICENSE [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, Sci2s group, 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

Downloads:

Reference manual: RSNNS.pdf
Package source: RSNNS_0.4-10.tar.gz
Windows binaries: r-devel: RSNNS_0.4-10.zip, r-release: RSNNS_0.4-10.zip, r-oldrel: RSNNS_0.4-10.zip
OS X El Capitan binaries: r-release: RSNNS_0.4-10.tgz
OS X Mavericks binaries: r-oldrel: RSNNS_0.4-10.tgz
Old sources: RSNNS archive

Reverse dependencies:

Reverse imports: nnetpredint, rasclass, semiArtificial
Reverse suggests: fscaret, mlr, NeuralNetTools

Linking:

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