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 321 downloads 15 exports 113 dependencies

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

TargetResultDate
Doc / VignettesOKOct 18 2024
R-4.5-winOKOct 18 2024
R-4.5-linuxOKOct 18 2024
R-4.4-winOKOct 18 2024
R-4.4-macOKOct 18 2024
R-4.3-winOKOct 18 2024
R-4.3-macOKOct 18 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.utilsR6rappdirsRColorBrewerRcppRcppArmadillorematch2rlangrmarkdownrpartrprojrootRPushbulletrstudioapisassscalessessioninfoSimDesignsnowstringistringrtestthattibbletidyrtidyselecttinytexutf8vctrsveganviridisviridisLitewaldowithrxfunyaml

Introduction to airt

Rendered fromairt.Rmdusingknitr::rmarkdownon Oct 18 2024.

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