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]

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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'))

Peer review:

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

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:

4.18 score 1 packages 8 scripts 365 downloads 15 exports 112 dependencies

Last updated 8 months agofrom:ff32b1c20b. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-winOKNov 17 2024
R-4.5-linuxOKNov 17 2024
R-4.4-winOKNov 17 2024
R-4.4-macOKNov 17 2024
R-4.3-winOKNov 17 2024
R-4.3-macOKNov 17 2024

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 Nov 17 2024.

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