Package: agua 0.1.4.9000

Qiushi Yan

agua: 'tidymodels' Integration with 'h2o'

Create and evaluate models using 'tidymodels' and 'h2o' <https://h2o.ai/>. The package enables users to specify 'h2o' as an engine for several modeling methods.

Authors:Max Kuhn [aut], Qiushi Yan [aut, cre], Steven Pawley [aut], Posit Software, PBC [cph, fnd]

agua_0.1.4.9000.tar.gz
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agua.pdf |agua.html✨
agua/json (API)
NEWS

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

Peer review:

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

On CRAN:

6.96 score 22 stars 69 scripts 916 downloads 35 exports 90 dependencies

Last updated 5 months agofrom:dfc7a13ad3. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 10 2024
R-4.5-winOKNov 10 2024
R-4.5-linuxOKNov 10 2024
R-4.4-winOKNov 10 2024
R-4.4-macOKNov 10 2024
R-4.3-winOKNov 10 2024
R-4.3-macOKNov 10 2024

Exports:%>%agua_backend_optionsas_h2oas_tibbleautoplotcollect_metricsextract_fit_engineextract_fit_parsnipget_leaderboardh2o_activationh2o_endh2o_get_frameh2o_get_modelh2o_predicth2o_predict_classificationh2o_predict_regressionh2o_removeh2o_remove_allh2o_runningh2o_splith2o_starth2o_trainh2o_train_autoh2o_train_gbmh2o_train_glmh2o_train_mlph2o_train_nbh2o_train_rfh2o_train_ruleh2o_train_xgboosth2o_xgboost_availablemember_weightsrank_resultsrefittidy

Dependencies:bitopsclasscliclockcodetoolscolorspacecpp11data.tablediagramdialsDiceDesigndigestdoFuturedplyrfansifarverforeachfurrrfuturefuture.applygenericsggplot2globalsgluegowerGPfitgtableh2ohardhatipredisobanditeratorsjsonliteKernSmoothlabelinglatticelavalhslifecyclelistenvlubridatemagrittrMASSMatrixmgcvmodelenvmunsellnlmennetnumDerivparallellyparsnippillarpkgconfigprettyunitsprodlimprogressrpurrrR6RColorBrewerRcppRCurlrecipesrlangrpartrsamplescalessfdshapeslidersparsevctrsSQUAREMstringistringrsurvivaltailortibbletidyrtidyselecttimechangetimeDatetunetzdbutf8vctrsviridisLitewarpwithrworkflowsyardstick

Introduction to agua

Rendered fromagua.Rmdusingknitr::rmarkdownon Nov 10 2024.

Last update: 2022-10-12
Started: 2022-07-12

Readme and manuals

Help Manual

Help pageTopics
Control model tuning via 'h2o::h2o.grid()'agua_backend_options
Data conversion toolsas_h2o as_tibble.H2OFrame
Plot rankings and metrics of H2O AutoML resultsautoplot.H2OAutoML autoplot.workflow
Prediction wrappers for h2oh2o_predict h2o_predict_classification h2o_predict_regression predict._H2OAutoML
Utility functions for interacting with the h2o serverh2o_end h2o_get_frame h2o_get_model h2o_remove h2o_remove_all h2o_running h2o_start h2o_xgboost_available
Model wrappers for h2oh2o_train h2o_train_auto h2o_train_gbm h2o_train_glm h2o_train_mlp h2o_train_nb h2o_train_rf h2o_train_rule h2o_train_xgboost
Tools for working with H2O AutoML resultscollect_metrics.H2OAutoML collect_metrics.workflow collect_metrics._H2OAutoML extract_fit_engine._H2OAutoML extract_fit_parsnip._H2OAutoML get_leaderboard member_weights rank_results.H2OAutoML rank_results.workflow rank_results._H2OAutoML refit.workflow refit._H2OAutoML tidy._H2OAutoML