Package: codez 2.0.0
codez: Torch Seq2Seq Encoder-Decoder Model for Time-Feature Analysis
Proposes Seq2seq Time-Feature Analysis using a torch Encoder-Decoder to project into latent space and a Forward Network to predict the next sequence, with dependency-light local support functions, tidy outputs and baseline backtesting helpers.
Authors:
codez_2.0.0.tar.gz
codez_2.0.0.zip(r-4.7-any)codez_2.0.0.zip(r-4.6-any)codez_2.0.0.zip(r-4.5-any)
codez_2.0.0.tgz(r-4.6-any)codez_2.0.0.tgz(r-4.5-any)
codez_2.0.0.tar.gz(r-4.7-any)codez_2.0.0.tar.gz(r-4.6-any)
codez_2.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
codez/json (API)
| # Install 'codez' in R: |
| install.packages('codez', repos = c('https://pigian.r-universe.dev', 'https://cloud.r-project.org')) |
- amzn_aapl_fb - Amzn_aapl_fb data set
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:9e2a5e224e. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 117 | ||
| source / vignettes | OK | 176 | ||
| linux-release-x86_64 | OK | 129 | ||
| macos-release-arm64 | OK | 100 | ||
| macos-oldrel-arm64 | OK | 79 | ||
| windows-devel | OK | 106 | ||
| windows-release | OK | 89 | ||
| windows-oldrel | OK | 63 | ||
| wasm-release | OK | 104 |
Exports:autoplotcodezcodez_controlcodez_forecast_tidyfit_codez
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| amzn_aapl_fb data set | amzn_aapl_fb |
| Create a codez plot object | autoplot |
| codez | codez-package codez |
| codez training controls | codez_control |
| Extract tidy forecasts from a codez result | codez_forecast_tidy |
| codez model methods | as.data.frame.codez_model autoplot.codez_model plot.codez_model predict.codez_model summary.codez_model |
| Fit a codez 2.0 model | fit_codez |
