Package: gt4ireval 2.0

gt4ireval: Generalizability Theory for Information Retrieval Evaluation

Provides tools to measure the reliability of an Information Retrieval test collection. It allows users to estimate reliability using Generalizability Theory and map those estimates onto well-known indicators such as Kendall tau correlation or sensitivity.

Authors:Julián Urbano [aut, cre]

gt4ireval_2.0.tar.gz
gt4ireval_2.0.zip(r-4.5)gt4ireval_2.0.zip(r-4.4)gt4ireval_2.0.zip(r-4.3)
gt4ireval_2.0.tgz(r-4.4-any)gt4ireval_2.0.tgz(r-4.3-any)
gt4ireval_2.0.tar.gz(r-4.5-noble)gt4ireval_2.0.tar.gz(r-4.4-noble)
gt4ireval_2.0.tgz(r-4.4-emscripten)gt4ireval_2.0.tgz(r-4.3-emscripten)
gt4ireval.pdf |gt4ireval.html
gt4ireval/json (API)

# Install 'gt4ireval' in R:
install.packages('gt4ireval', repos = c('https://julian-urbano.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/julian-urbano/gt4ireval/issues

Datasets:

On CRAN:

10 exports 5 stars 1.15 score 0 dependencies 7 scripts 788 downloads

Last updated 7 years agofrom:8ec8ebbb42. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 04 2024
R-4.5-winOKSep 04 2024
R-4.5-linuxOKSep 04 2024
R-4.4-winOKSep 04 2024
R-4.4-macOKSep 04 2024
R-4.3-winOKSep 04 2024
R-4.3-macOKSep 04 2024

Exports:dstudygstudygt2asensgt2majorgt2minorgt2powergt2rmsegt2rsensgt2taugt2tauAP

Dependencies:

gt4ireval: Generalizability Theory for Information Retrieval Evaluation

Rendered fromgt4ireval.Rmdusingknitr::rmarkdownon Sep 04 2024.

Last update: 2017-03-06
Started: 2017-03-06