Package: Sstack 1.0.1

Sstack: Bootstrap Stacking of Random Forest Models for Heterogeneous Data

Generates and predicts a set of linearly stacked Random Forest models using bootstrap sampling. Individual datasets may be heterogeneous (not all samples have full sets of features). Contains support for parallelization but the user should register their cores before running. This is an extension of the method found in Matlock (2018) <doi:10.1186/s12859-018-2060-2>.

Authors:Kevin Matlock, Raziur Rahman

Sstack_1.0.1.tar.gz
Sstack_1.0.1.zip(r-4.7-any)Sstack_1.0.1.zip(r-4.6-any)Sstack_1.0.1.zip(r-4.5-any)
Sstack_1.0.1.tgz(r-4.6-any)Sstack_1.0.1.tgz(r-4.5-any)
Sstack_1.0.1.tar.gz(r-4.7-any)Sstack_1.0.1.tar.gz(r-4.6-any)
Sstack_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
Sstack/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 3 scripts 218 downloads 4 exports 20 dependencies

Last updated from:898c6526a1. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK126
source / vignettesOK141
linux-release-x86_64OK114
macos-release-arm64OK117
macos-oldrel-arm64OK168
windows-develOK77
windows-releaseOK67
windows-oldrelOK65
wasm-releaseOK92

Exports:BSHorizontalStackBSstackBSstack_predictBSVerticalStack

Dependencies:clicodetoolsdoParalleldplyrforeachgenericsglueiteratorslifecyclemagrittrpillarpkgconfigR6randomForestrlangtibbletidyselectutf8vctrswithr