Package: sboost 0.1.2

sboost: Machine Learning with AdaBoost on Decision Stumps

Creates classifier for binary outcomes using Adaptive Boosting (AdaBoost) algorithm on decision stumps with a fast C++ implementation. For a description of AdaBoost, see Freund and Schapire (1997) <doi:10.1006/jcss.1997.1504>. This type of classifier is nonlinear, but easy to interpret and visualize. Feature vectors may be a combination of continuous (numeric) and categorical (string, factor) elements. Methods for classifier assessment, predictions, and cross-validation also included.

Authors:Jadon Wagstaff [aut, cre]

sboost_0.1.2.tar.gz
sboost_0.1.2.zip(r-4.7)sboost_0.1.2.zip(r-4.6)sboost_0.1.2.zip(r-4.5)
sboost_0.1.2.tgz(r-4.6-x86_64)sboost_0.1.2.tgz(r-4.6-arm64)sboost_0.1.2.tgz(r-4.5-x86_64)sboost_0.1.2.tgz(r-4.5-arm64)
sboost_0.1.2.tar.gz(r-4.7-arm64)sboost_0.1.2.tar.gz(r-4.7-x86_64)sboost_0.1.2.tar.gz(r-4.6-arm64)sboost_0.1.2.tar.gz(r-4.6-x86_64)
sboost_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
sboost/json (API)

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

Bug tracker:https://github.com/jadonwagstaff/sboost/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

3.00 score 2 stars 8 scripts 234 downloads 3 exports 16 dependencies

Last updated from:aee4038080. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK142
linux-devel-x86_64OK120
source / vignettesOK173
linux-release-arm64OK124
linux-release-x86_64OK136
macos-release-arm64OK108
macos-release-x86_64OK500
macos-oldrel-arm64OK138
macos-oldrel-x86_64OK327
windows-develOK104
windows-releaseOK115
windows-oldrelOK111
wasm-releaseOK108

Exports:assesssboostvalidate

Dependencies:clidplyrgenericsgluelifecyclemagrittrpillarpkgconfigR6Rcpprlangtibbletidyselectutf8vctrswithr