Package: stacking 0.2.1

stacking: Building Predictive Models with Stacking

Building predictive models with stacking which is a type of ensemble learning. Learners can be specified from those implemented in 'caret'. For more information of the package, see Nukui and Onogi (2023) <doi:10.1101/2023.06.06.543970>.

Authors:Taichi Nukui [aut, cph], Tomohiro Ishibashi [aut, cph], Akio Onogi [aut, cre, cph]

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stacking.pdf |stacking.html✨
stacking/json (API)

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

Bug tracker:https://github.com/onogi/stacking/issues

On CRAN:

Conda:

3.60 score 4 stars 3 scripts 250 downloads 5 exports 76 dependencies

Last updated 2 months agofrom:f4a83161e0. Checks:1 OK, 8 ERROR. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 08 2025
R-4.5-winERRORMar 08 2025
R-4.5-macERRORMar 08 2025
R-4.5-linuxERRORMar 08 2025
R-4.4-winERRORMar 08 2025
R-4.4-macERRORMar 08 2025
R-4.4-linuxERRORMar 08 2025
R-4.3-winERRORMar 08 2025
R-4.3-macERRORMar 08 2025

Exports:stacking_predictstacking_traintrain_basemodeltrain_basemodel_coretrain_metamodel

Dependencies:caretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrpartscalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr