Package: orbital 0.7.0.9000

Emil Hvitfeldt

orbital: Predict with 'tidymodels' Workflows in Databases

Turn 'tidymodels' workflows into objects containing the sufficient sequential equations to perform predictions. These smaller objects allow for low dependency prediction locally or directly in databases.

Authors:Emil Hvitfeldt [aut, cre], Posit Software, PBC [cph, fnd]

orbital_0.7.0.9000.tar.gz
orbital_0.7.0.9000.zip(r-4.7-any)orbital_0.7.0.9000.zip(r-4.6-any)orbital_0.7.0.9000.zip(r-4.5-any)
orbital_0.7.0.9000.tgz(r-4.6-any)orbital_0.7.0.9000.tgz(r-4.5-any)
orbital_0.7.0.9000.tar.gz(r-4.7-any)orbital_0.7.0.9000.tar.gz(r-4.6-any)
orbital_0.7.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
orbital/json (API)

# Install 'orbital' in R:
install.packages('orbital', repos = c('https://tidymodels.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tidymodels/orbital/issues

Pkgdown/docs site:https://orbital.tidymodels.org

On CRAN:

Conda:

7.84 score 51 stars 57 scripts 611 downloads 9 exports 15 dependencies

Last updated from:3b0a1649a0. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE474
source / vignettesOK286
linux-releaseNOTE464
macos-releaseNOTE346
macos-oldrelNOTE305
windows-develNOTE545
windows-releaseNOTE550
windows-oldrelNOTE701
wasm-releaseOK203

Exports:augmentestimate_orbital_sizeorbitalorbital_dtorbital_inlineorbital_json_readorbital_json_writeorbital_r_funorbital_sql

Dependencies:clidplyrgenericsgluelifecyclemagrittrpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithr

Supported Models and recipes steps
Supported models | Why some models support one classification type but not the other | Ensembles | Recipes steps | tailor adjustments
Rendered fromsupported-models.Rmdusingknitr::rmarkdown

Last update: 2026-09-30
Started: 2024-07-25

Neural networks
Supported layers | Input names | Mode, type, and lvl | Extracting an intermediate layer | Multi-output networks | torch | keras3
Rendered fromneural-networks.Rmdusingknitr::rmarkdown

Last update: 2026-09-24
Started: 2026-09-24

Parallel tree evaluation in databases
The problem | The solution | Batched summation | Example | Supported models | Models where the argument has no effect | Output behavior | When to use | Good candidates for separate_trees = TRUE | When to stick with the default | Tradeoffs | Benchmarking recommendation
Rendered fromseparate-trees.Rmdusingknitr::rmarkdown

Last update: 2026-08-27
Started: 2026-02-24

Readme and manuals

Help Manual

Help pageTopics
Augment using orbital objectsaugment.orbital_class
Estimate orbital expression character countestimate_orbital_size estimate_orbital_size.brulee_mlp estimate_orbital_size.catboost.Model estimate_orbital_size.constparty estimate_orbital_size.earth estimate_orbital_size.glm estimate_orbital_size.glmnet estimate_orbital_size.keras.src.models.sequential.Sequential estimate_orbital_size.lgb.Booster estimate_orbital_size.lm estimate_orbital_size.nn_sequential estimate_orbital_size.randomForest estimate_orbital_size.ranger estimate_orbital_size.recipe estimate_orbital_size.rpart estimate_orbital_size.tailor estimate_orbital_size.workflow estimate_orbital_size.xgb.Booster
Turn tidymodels objects into orbital objectsorbital
Convert to data.table codeorbital_dt
Convert orbital objects to quosuresorbital_inline
Read orbital json fileorbital_json_read
Save orbital object as json fileorbital_json_write
Turn orbital object into a R functionorbital_r_fun
Convert to SQL codeorbital_sql
Prediction using orbital objectspredict.orbital_class