Recurrent Neural Network

Implementation of a Recurrent Neural Network architectures in native R, including Long Short-Term Memory (Hochreiter and Schmidhuber, ), Gated Recurrent Unit (Chung et al., ) and vanilla RNN.

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Implementation of a Recurrent Neural Network in R.


The stable version can be installed from CRAN using:


The development version, to be used at your peril, can be installed from GitHub using the devtools package.

if (!require('devtools')) install.packages('devtools')


Following installation, the package can be loaded using:


For general information on using the package, please refer to the help files.


There is also a long form vignette available using:


Additional Information

An overview of the changes is available in the NEWS file.


There is a dedicated website with information hosted on my personal website.


Development takes place on the GitHub page.

Bugs can be filed on the issues page on GitHub.


rnn 0.8.1

  • fix documentation: working examples

rnn 0.8.0

  • add LSTM

  • add GRU

  • complete code refactoring

rnn 0.7.0

  • implement multilayer option by Dimitri Fichou

rnn 0.5.0

  • rename rnn to trainr

  • trainr outputs model

  • add predictr function to use trainr model

  • defaults to no printing

rnn 0.3.0

  • switch to internal methods for binary representation

  • add choice of print methods

rnn 0.3.0

  • modified print method, highlights the column-by-column input method

rnn 0.2.0

  • generalised to use user training data instead of generated

rnn 0.1.0

  • initial release

Reference manual

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1.5.0 by Bastiaan Quast, 15 days ago,

Report a bug at

Browse source code at

Authors: Bastiaan Quast [aut, cre] , Dimitri Fichou [aut]

Documentation:   PDF Manual  

Task views:

GPL-3 license

Imports sigmoid, shiny

Suggests testthat, knitr, rmarkdown

Imported by SLBDD.

See at CRAN