Package: tidypredict 1.1.0.9000

Emil Hvitfeldt

tidypredict: Run Predictions Inside the Database

It parses a fitted 'R' model object, and returns a formula in 'Tidy Eval' code that calculates the predictions. It works with several databases back-ends because it leverages 'dplyr' and 'dbplyr' for the final 'SQL' translation of the algorithm. It currently supports lm(), glm(), randomForest(), ranger(), rpart(), earth(), xgb.Booster.complete(), lgb.Booster(), catboost.Model(), cubist(), and ctree() models.

Authors:Emil Hvitfeldt [aut, cre], Edgar Ruiz [aut], Max Kuhn [aut]

tidypredict_1.1.0.9000.tar.gz
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tidypredict_1.1.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
tidypredict/json (API)
NEWS

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

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

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

On CRAN:

Conda:

dbplyrdplyrpurrrrlang

12.05 score 263 stars 2 packages 294 scripts 1.4k downloads 27 exports 26 dependencies

Last updated from:5d33183137. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK195
source / vignettesOK234
linux-release-x86_64OK166
macos-release-arm64OK105
macos-oldrel-arm64OK135
windows-develOK125
windows-releaseOK113
windows-oldrelOK117
wasm-releaseOK130

Exports:.build_case_when_tree.build_linear_pred.build_nested_case_when_tree.extract_catboost_trees.extract_earth_multiclass.extract_glmnet_multiclass.extract_lgb_trees.extract_partykit_classprob.extract_ranger_classprob.extract_ranger_trees.extract_rf_classprob.extract_rf_trees.extract_rpart_classprob.extract_xgb_trees.partykit_tree_info_full.rpart_tree_info_fullacceptable_formulaas_parsed_modelparse_modelset_catboost_categoriestidytidypredict_fittidypredict_intervaltidypredict_sqltidypredict_sql_intervaltidypredict_testtidypredict_to_column

Dependencies:clicpp11dplyrevaluategenericsgluehighrjsonliteknitrlifecyclemagrittrpillarpkgconfigpurrrR6rlangstringistringrtibbletidyrtidyselectutf8vctrswithrxfunyaml

catboost models

Rendered fromcatboost.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2026-02-25
Started: 2026-02-12

Create a regression spec - version 2

Rendered fromregression.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2022-05-31
Started: 2019-07-06

Create a tree spec - version 2

Rendered fromtree.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2022-05-31
Started: 2019-07-06

Cubist models

Rendered fromcubist.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2026-02-25
Started: 2019-07-07

Database write-back

Rendered fromsql.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2023-10-31
Started: 2018-01-02

Decision trees, using rpart

Rendered fromrpart.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2026-02-20
Started: 2026-02-20

Float precision at split boundaries

Rendered fromfloat-precision.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2026-02-25
Started: 2026-02-25

Generalized Linear Regression

Rendered fromglm.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2023-10-31
Started: 2017-12-27

glmnet models

Rendered fromglmnet.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2025-11-07
Started: 2025-11-07

How tidypredict generates tree formulas

Rendered fromtree-internals.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2026-02-20
Started: 2026-02-20

LightGBM models

Rendered fromlightgbm.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2026-02-25
Started: 2026-02-11

Linear Regression

Rendered fromlm.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2025-11-04
Started: 2017-12-27

MARS models via the earth package

Rendered frommars.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2023-10-31
Started: 2019-07-07

Non-R Models

Rendered fromnon-r.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2022-05-31
Started: 2019-07-12

Random Forest

Rendered fromrf.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2025-11-26
Started: 2019-07-03

Random Forest, using Ranger

Rendered fromranger.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2025-11-26
Started: 2018-02-20

Save and re-load models

Rendered fromsave.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2022-05-31
Started: 2017-12-30

XGBoost models

Rendered fromxgboost.Rmdusingknitr::rmarkdownon May 21 2026.

Last update: 2026-02-25
Started: 2019-07-07