Package: stacks 1.0.5.9000

Simon Couch

stacks: Tidy Model Stacking

Model stacking is an ensemble technique that involves training a model to combine the outputs of many diverse statistical models, and has been shown to improve predictive performance in a variety of settings. 'stacks' implements a grammar for 'tidymodels'-aligned model stacking.

Authors:Simon Couch [aut, cre], Max Kuhn [aut], Posit Software, PBC [cph, fnd]

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stacks.pdf |stacks.html
stacks/json (API)
NEWS

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

Peer review:

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

Pkgdown site:https://stacks.tidymodels.org

Datasets:

On CRAN:

11.56 score 295 stars 860 scripts 1.9k downloads 22 mentions 28 exports 91 dependencies

Last updated 2 months agofrom:8c72db52f1. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 22 2024
R-4.5-winOKDec 22 2024
R-4.5-linuxOKDec 22 2024
R-4.4-winOKDec 22 2024
R-4.4-macOKDec 22 2024
R-4.3-winOKDec 22 2024
R-4.3-macOKDec 22 2024

Exports:%>%add_candidatesaugmentautoplotaxe_callaxe_call.model_stackaxe_ctrlaxe_ctrl.model_stackaxe_dataaxe_data.model_stackaxe_envaxe_env.model_stackaxe_fittedaxe_fitted.model_stackblend_predictionsbuild_linear_predictorbutchercollect_parameterscontrol_stack_bayescontrol_stack_gridcontrol_stack_resamplesfit_membersget_expressionspredict.data_stackpredict.model_stackprediction_eqnstack_predictstacks

Dependencies:butcherclasscliclockcodetoolscolorspacecpp11crayondata.tablediagramdialsDiceDesigndigestdoFuturedplyrfansifarverforeachfurrrfuturefuture.applygenericsggplot2glmnetglobalsgluegowerGPfitgtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalhslifecyclelistenvlobstrlubridatemagrittrMASSMatrixmgcvmodelenvmunsellnlmennetnumDerivparallellyparsnippillarpkgconfigprettyunitsprodlimprogressrpurrrR6RColorBrewerRcppRcppEigenrecipesrlangrpartrsamplescalessfdshapeslidersparsevctrsSQUAREMstringistringrsurvivaltailortibbletidyrtidyselecttimechangetimeDatetunetzdbutf8vctrsviridisLitewarpwithrworkflowsyardstick

Classification Models With stacks

Rendered fromclassification.Rmdusingknitr::rmarkdownon Dec 22 2024.

Last update: 2024-08-15
Started: 2020-07-14

Getting Started With stacks

Rendered frombasics.Rmdusingknitr::rmarkdownon Dec 22 2024.

Last update: 2024-08-15
Started: 2020-07-07

Readme and manuals

Help Manual

Help pageTopics
Add model definitions to a data stackadd_candidates
Augment a model stackaugment.model_stack
Plot results of a stacked ensemble model.autoplot.linear_stack
Axing a model_stack.axe_call.model_stack axe_ctrl.model_stack axe_data.model_stack axe_env.model_stack axe_fitted.model_stack axe_model_stack
Determine stacking coefficients from a data stackblend_predictions
Collect candidate parameters and stacking coefficientscollect_parameters collect_parameters.data_stack collect_parameters.default collect_parameters.model_stack
Control wrapperscontrol_stack control_stack_bayes control_stack_grid control_stack_resamples
Example Objectsclass_folds class_res_nn class_res_rf example_data log_res_nn log_res_rf reg_folds reg_res_lr reg_res_sp reg_res_svm tree_frogs_class_test tree_frogs_reg_test
Fit model stack members with non-zero stacking coefficientsfit_members
Obtain prediction equations for all possible values of typeget_expressions get_expressions._elnet get_expressions._lognet get_expressions._multnet
Predicting with a model stackpredict.data_stack
Predicting with a model stackpredict.model_stack
Initialize a Stackstacks
stacks: Tidy Model Stackingstacks-package stacks_description stacks_package
Tree frog embryo hatching datatree_frogs