Package: agua 0.1.4.9000
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:
agua_0.1.4.9000.tar.gz
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agua_0.1.4.9000.tgz(r-4.4-any)agua_0.1.4.9000.tgz(r-4.3-any)
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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')) |
Bug tracker:https://github.com/tidymodels/agua/issues
Pkgdown site:https://agua.tidymodels.org
Last updated 7 months agofrom:dfc7a13ad3. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 10 2024 |
R-4.5-win | OK | Dec 10 2024 |
R-4.5-linux | OK | Dec 10 2024 |
R-4.4-win | OK | Dec 10 2024 |
R-4.4-mac | OK | Dec 10 2024 |
R-4.3-win | OK | Dec 10 2024 |
R-4.3-mac | OK | Dec 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
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Control model tuning via 'h2o::h2o.grid()' | agua_backend_options |
Data conversion tools | as_h2o as_tibble.H2OFrame |
Plot rankings and metrics of H2O AutoML results | autoplot.H2OAutoML autoplot.workflow |
Prediction wrappers for h2o | h2o_predict h2o_predict_classification h2o_predict_regression predict._H2OAutoML |
Utility functions for interacting with the h2o server | h2o_end h2o_get_frame h2o_get_model h2o_remove h2o_remove_all h2o_running h2o_start h2o_xgboost_available |
Model wrappers for h2o | h2o_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 results | collect_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 |