RSNNS: Neural Networks in R 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: 0.4-9
Depends: R (≥ 2.10.0), methods, Rcpp (≥ 0.8.5)
LinkingTo: Rcpp
Suggests: scatterplot3d, NeuralNetTools
Published: 2016-12-16
Author: Christoph Bergmeir and José M. Benítez
Maintainer: Christoph Bergmeir <c.bergmeir at>
License: LGPL-2 | LGPL-2.1 | LGPL-3 | file LICENSE [expanded from: LGPL (≥ 2) | file LICENSE]
NeedsCompilation: yes
Citation: RSNNS citation info
Materials: ChangeLog
In views: MachineLearning
CRAN checks: RSNNS results


Reference manual: RSNNS.pdf
Package source: RSNNS_0.4-9.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: RSNNS_0.4-9.tgz, r-oldrel: RSNNS_0.4-9.tgz
Old sources: RSNNS archive

Reverse dependencies:

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


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