Package: baguette 1.0.2.9000

Max Kuhn

baguette:Efficient Model Functions for Bagging

Tree- and rule-based models can be bagged (<doi:10.1007/BF00058655>) using this package and their predictions equations are stored in an efficient format to reduce the model objects size and speed.

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

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baguette/json (API)
NEWS

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

Peer review:

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

On CRAN:

7 exports 24 stars 2.53 score 66 dependencies 842 downloads

Last updated 3 months agofrom:ad9df1d3a2

Exports:%>%baggerclass_costcontrol_bagnnet_imp_garsonvar_impvar_imp.bagger

Dependencies:butcherC50clicodetoolscolorspacecpp11crayonCubistdialsDiceDesigndigestdplyrfansifarverFormulafurrrfuturegenericsggplot2globalsgluegtablehardhatinumisobandlabelinglatticelibcoinlifecyclelistenvlobstrmagrittrMASSMatrixmgcvmunsellmvtnormnlmeparallellyparsnippartykitpillarpkgconfigplyrprettyunitspurrrR6RColorBrewerRcppreshape2rlangrpartrsamplescalessliderstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewarpwithr

Readme and manuals

Help Manual

Help pageTopics
Bagging functionsbagger bagger.data.frame bagger.default bagger.formula bagger.matrix bagger.recipe
Cost parameter for minority classclass_cost
Controlling the bagging processcontrol_bag
Predictions from a bagged modelpredict.bagger
Obtain variable importance scoresvar_imp.bagger