Package: airt 0.2.3

Sevvandi Kandanaarachchi

airt: Evaluation of Algorithm Collections Using Item Response Theory

An evaluation framework for algorithm portfolios using Item Response Theory (IRT). We use continuous and polytomous IRT models to evaluate algorithms and introduce algorithm characteristics such as stability, effectiveness and anomalousness (Kandanaarachchi, Smith-Miles 2020) <doi:10.13140/RG.2.2.11363.09760>.

Authors:Sevvandi Kandanaarachchi [aut, cre]

airt_0.2.3.tar.gz
airt_0.2.3.zip(r-4.7)airt_0.2.3.zip(r-4.6)airt_0.2.3.zip(r-4.5)
airt_0.2.3.tgz(r-4.6-any)airt_0.2.3.tgz(r-4.5-any)
airt_0.2.3.tar.gz(r-4.7-any)airt_0.2.3.tar.gz(r-4.6-any)
airt_0.2.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
airt/json (API)

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

Bug tracker:https://github.com/sevvandi/airt/issues

Pkgdown/docs site:https://sevvandi.github.io

Datasets:
  • classification_cts - A dataset containing classification algorithm performance data in a continuous format.
  • classification_poly - A dataset containing classification algorithm performance data in a polytomous format.

On CRAN:

Conda:

4.18 score 1 packages 8 scripts 314 downloads 15 exports 117 dependencies

Last updated from:ff32b1c20b. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK191
source / vignettesOK239
linux-release-x86_64OK186
macos-release-arm64OK148
macos-oldrel-arm64OK141
windows-develOK139
windows-releaseOK145
windows-oldrelOK146
wasm-releaseOK139

Exports:algo_effectiveness_crmalgo_effectiveness_polyautoplotcirtmodeleffectiveness_crmeffectiveness_polyheatmaps_crmlatent_trait_analysismake_polyIRT_datamodel_goodness_crmmodel_goodness_for_algo_crmmodel_goodness_for_algo_polymodel_goodness_polypirtmodeltracelines_poly

Dependencies:audiobackportsbase64encbeeprbriobslibcachemcallrcheckmateclassclicliprclustercodetoolscolorspacecpp11crayondata.tabledcurverDerivdescdiffobjdigestdplyre1071EstCRMevaluatefarverfastmapfontawesomeforeignFormulafsfuturefuture.applygenericsggplot2globalsglueGPArotationgridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclelistenvmagrittrMASSMatrixmemoisemgcvmimemiraimirtnanonextnlmennetparallellypbapplypermutepillarpkgbuildpkgconfigpkgloadpracmapraiseprocessxprogressrproxypspurrrqs2R.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcppRcppArmadilloRcppParallelrlangrmarkdownrpartrprojrootrstudioapiS7sassscalessessioninfoSimDesignsplines2stringfishstringistringrtestthattibbletidyrtidyselecttinytexutf8vctrsveganviridisLitewaldowithrxfunyaml

Introduction to airt

Rendered fromairt.Rmdusingknitr::rmarkdownon May 11 2026.

Last update: 2024-03-21
Started: 2020-03-22