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]

stacking_0.2.1.tar.gz
stacking_0.2.1.zip(r-4.7-any)stacking_0.2.1.zip(r-4.6-any)stacking_0.2.1.zip(r-4.5-any)
stacking_0.2.1.tgz(r-4.6-any)stacking_0.2.1.tgz(r-4.5-any)
stacking_0.2.1.tar.gz(r-4.7-any)stacking_0.2.1.tar.gz(r-4.6-any)
stacking_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
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:

3.30 score 4 stars 4 scripts 268 downloads 5 exports 73 dependencies

Last updated from:f4a83161e0. Checks:7 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develERROR170
source / vignettesOK204
linux-releaseERROR137
macos-releaseERROR139
macos-oldrelERROR159
windows-develERROR101
windows-releaseERROR133
windows-oldrelERROR112
wasm-releaseOK124

Exports:stacking_predictstacking_traintrain_basemodeltrain_basemodel_coretrain_metamodel

Dependencies:caretclasscliclockcodetoolscpp11data.tablediagramdigestdplyre1071farverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixModelMetricsnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrpartS7scalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr