codez: Seq2Seq Encoder-Decoder Model for Time-Feature Analysis Based on Tensorflow

Proposes Seq2seq Time-Feature Analysis using an Encoder-Decoder to project into latent space and a Forward Network to predict the next sequence.

Version: 1.0.0
Depends: R (≥ 3.6)
Imports: purrr (≥ 0.3.4), abind (≥ 1.4-5), ggplot2 (≥ 3.3.6), readr (≥ 2.1.2), fANCOVA (≥ 0.6-1), imputeTS (≥ 3.2), modeest (≥ 2.4.0), scales (≥ 1.1.1), tictoc (≥ 1.0.1), tensorflow (≥ 2.9.0), keras (≥ 2.9.0), moments (≥ 0.14), narray (≥ 0.4.1.1), fastDummies (≥ 1.6.3), entropy (≥ 1.3.1), philentropy (≥ 0.5.0), greybox (≥ 1.0.1), lubridate (≥ 1.7.10)
Suggests: testthat (≥ 3.0.0), reticulate (≥ 1.26)
Published: 2022-09-23
Author: Giancarlo Vercellino [aut, cre, cph]
Maintainer: Giancarlo Vercellino <giancarlo.vercellino at gmail.com>
License: GPL-3
URL: https://rpubs.com/giancarlo_vercellino/codez
NeedsCompilation: no
Materials: NEWS
CRAN checks: codez results

Documentation:

Reference manual: codez.pdf

Downloads:

Package source: codez_1.0.0.tar.gz
Windows binaries: r-devel: codez_1.0.0.zip, r-release: codez_1.0.0.zip, r-oldrel: not available
macOS binaries: r-release (arm64): codez_1.0.0.tgz, r-oldrel (arm64): codez_1.0.0.tgz, r-release (x86_64): codez_1.0.0.tgz, r-oldrel (x86_64): codez_1.0.0.tgz

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