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
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airt.pdf |airt.html
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 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 376 downloads 15 exports 112 dependencies

Last updated 12 months agofrom:ff32b1c20b. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 15 2025
R-4.5-winOKFeb 15 2025
R-4.5-macOKFeb 15 2025
R-4.5-linuxOKFeb 15 2025
R-4.4-winOKFeb 15 2025
R-4.4-macOKFeb 15 2025
R-4.3-winOKFeb 15 2025
R-4.3-macOKFeb 15 2025

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:audiobackportsbase64encbeeprbriobslibcachemcallrcheckmatecliclustercodetoolscolorspacecpp11crayoncurldata.tabledcurverDerivdescdiffobjdigestdplyrEstCRMevaluatefansifarverfastmapfontawesomeforeignFormulafsfuturefuture.applygenericsggplot2globalsglueGPArotationgridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclelistenvmagrittrMASSMatrixmemoisemgcvmimemirtmunsellnlmennetparallellypbapplypermutepillarpkgbuildpkgconfigpkgloadpracmapraiseprocessxprogressrpspurrrR.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcppRcppArmadillorlangrmarkdownrpartrprojrootRPushbulletrstudioapisassscalessessioninfoSimDesignsnowstringistringrtestthattibbletidyrtidyselecttinytexutf8vctrsveganviridisviridisLitewaldowithrxfunyaml

Introduction to airt

Rendered fromairt.Rmdusingknitr::rmarkdownon Feb 15 2025.

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