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The LSTM (Long Short-Term Memory) model is a Recurrent Neural Network (RNN) based architecture that is widely used for time series forecasting. Customizable configurations for the model are allowed, improving the capabilities and usability of this model compared to other packages. This package is based on 'keras' and 'tensorflow' modules and the algorithm of Paul and Garai (2021) <doi:10.1007/s00500-021-06087-4>.
| Version: | 1.0.5 |
| Imports: | keras, tensorflow, tsutils, stats, abind |
| Published: | 2024-09-06 |
| DOI: | 10.32614/CRAN.package.TSLSTMplus |
| Author: | Jaime Pizarroso Gonzalo [aut, ctb, cre], Antonio Muñoz San Roque [aut] |
| Maintainer: | Jaime Pizarroso Gonzalo <jpizarroso at comillas.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| In views: | TimeSeries |
| CRAN checks: | TSLSTMplus results |
| Reference manual: | TSLSTMplus.pdf |
| Package source: | TSLSTMplus_1.0.5.tar.gz |
| Windows binaries: | r-devel: TSLSTMplus_1.0.5.zip, r-release: TSLSTMplus_1.0.5.zip, r-oldrel: TSLSTMplus_1.0.5.zip |
| macOS binaries: | r-release (arm64): TSLSTMplus_1.0.5.tgz, r-oldrel (arm64): TSLSTMplus_1.0.5.tgz, r-release (x86_64): TSLSTMplus_1.0.5.tgz, r-oldrel (x86_64): TSLSTMplus_1.0.5.tgz |
| Old sources: | TSLSTMplus archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.