Implementation of a Recurrent Neural Network architectures in native R, including Long Short-Term Memory (Hochreiter and Schmidhuber, <doi:10.1162/neco.1997.9.8.1735>), Gated Recurrent Unit (Chung et al., <arXiv:1412.3555>) and vanilla RNN.
| Version: | 1.4.0 |
| Depends: | R (≥ 3.2.2) |
| Imports: | sigmoid, shiny |
| Suggests: | testthat, knitr, rmarkdown |
| Published: | 2020-07-03 |
| Author: | Bastiaan Quast [aut, cre], Dimitri Fichou [aut] |
| Maintainer: | Bastiaan Quast <bquast at gmail.com> |
| BugReports: | https://github.com/bquast/rnn/issues |
| License: | GPL-3 |
| URL: | http://qua.st/rnn, https://github.com/bquast/rnn |
| NeedsCompilation: | no |
| Citation: | rnn citation info |
| Materials: | README NEWS |
| CRAN checks: | rnn results |
| Reference manual: | rnn.pdf |
| Vignettes: |
GRU units LSTM units Basic Recurrent Neural Network Recurrent Neural Network RNN units Sinus and Cosinus |
| Package source: | rnn_1.4.0.tar.gz |
| Windows binaries: | r-devel: rnn_1.4.0.zip, r-release: rnn_1.4.0.zip, r-oldrel: rnn_1.4.0.zip |
| macOS binaries: | r-release: rnn_1.4.0.tgz, r-oldrel: rnn_1.4.0.tgz |
| Old sources: | rnn archive |
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