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 | 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

Documentation:

Reference manual:

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, FRI, noisemodel, rasclass, semiArtificial, TSPred
Reverse suggests:	flowml, fscaret, mistyR, mlr, NeuralNetTools, NeuralSens
Reverse enhances:	vip

Linking:

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