The rnn package in R

To implement RNN in an R environment, we can use the rnn package available through CRAN. This package is widely used to implement an RNN. A brief description of the rnn package, extracted from the official documentation, is shown in the following table:

rnn: Recurrent Neural Network

Description:

Implementation of an RNN in R

Details:

Package: rnn Type: Package Version: 0.8.0 Date: 2016-09-11 License: GPL-3

Authors:

Bastiaan Quast Dimitri Fichou

The main functions used from the rnn package are shown in this table:

predict_rnn	Predicts the output of an RNN model: predict_rnn(model, X, hidden = FALSE, real_output = T, ...)
run.rnn_demo	A function to launch the rnn_demo app​: run.rnn_demo(port = NULL)
trainr	This trains the RNN. The model is used by the predictr function.
predictr	This predicts the output of an RNN model: predictr(model, X, hidden = FALSE, real_output = T, ...)

 

 

As always, to be able to use a library, we must first install and then load it into our script.

Note

Remember, to...