Package: stacking 0.1.3

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>. Packages caret, parallel, snow, and packages for base and meta learners should be installed.

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

stacking_0.1.3.tar.gz
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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'))

Peer review:

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

On CRAN:

3.30 score 4 stars 3 scripts 224 downloads 5 exports 75 dependencies

Last updated 2 months agofrom:6c59c508b3. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 10 2024
R-4.5-winOKNov 10 2024
R-4.5-linuxOKNov 10 2024
R-4.4-winOKNov 10 2024
R-4.4-macOKNov 10 2024
R-4.3-winOKNov 10 2024
R-4.3-macOKNov 10 2024

Exports:stacking_predictstacking_traintrain_basemodeltrain_basemodel_coretrain_metamodel

Dependencies:caretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr