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.

rnn

Implementation of a Recurrent Neural Network in R.

Demonstration

Installation

The stable version can be installed from CRAN using:

install.packages('rnn')

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

if (!require('remotes')) install.packages('remotes')
remotes::install_github('bquast/rnn')

Usage

Following installation, the package can be loaded using:

library(rnn)

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

help('trainr')
help('predictr')
help(package='rnn')

There is also a long form vignette available using:

vignette('rnn')

Additional Information

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

news(package='rnn')

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

Development

Development takes place on the GitHub page.

https://github.com/bquast/rnn/

Bugs can be filed on the issues page on GitHub.

https://github.com/bquast/rnn/issues