Neural networks in R using the Stuttgart neural network simulator: RSNNS

Christoph Bergmeir, José M. Benítez

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Neural networks are important standard machine learning procedures for classification and regression. We describe the R package RSNNS that provides a convenient interface to the popular Stuttgart Neural Network Simulator SNNS. The main features are (a) encapsulation of the relevant SNNS parts in a C++ class, for sequential and parallel usage of difierent networks, (b) accessibility of all of the SNNS algorithmic functionality from R using a low-level interface, and (c) a high-level interface for convenient, R-style usage of many standard neural network procedures. The package also includes functions for visualization and analysis of the models and the training procedures, as well as functions for data input/output from/to the original SNNS file formats.

Original languageEnglish
JournalJournal of Statistical Software
Volume46
Issue number7
Publication statusPublished - Jan 2012
Externally publishedYes

Keywords

  • Neural networks
  • R
  • RSNNS
  • SNNS

Cite this

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Neural networks in R using the Stuttgart neural network simulator : RSNNS. / Bergmeir, Christoph; Benítez, José M.

In: Journal of Statistical Software, Vol. 46, No. 7, 01.2012.

Research output: Contribution to journalArticleResearchpeer-review

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