Package: Usmile 0.2.0

Usmile: Threshold-Free Class-Specific Comparison of Binary Classifiers

Implements the U-smile methodology for threshold-free, class-specific comparison of probabilistic binary classifiers. The package quantifies prediction improvement and worsening separately for non-events and events using the Brier alteration (BA), relative Brier (RB), improvement proportion (I) coefficients, and relative likelihood ratio (rLR) coefficients, and provides U-smile, prediction improvement-worsening, receiver operating characteristic, and precision-recall plots. The original U-smile framework is described in Kubiak et al. (2024) <doi:10.1371/journal.pone.0303276>, its three-level extension for imbalanced binary classification in Wieckowska et al. (2025) <doi:10.1371/journal.pone.0321661>, and the likelihood-based extension in Wieckowska and Guzik (2026) <doi:10.1038/s41598-026-40545-z>.

Authors:Barbara Więckowska [aut, cre]

Usmile_0.2.0.tar.gz
Usmile_0.2.0.zip(r-4.7-any)Usmile_0.2.0.zip(r-4.6-any)Usmile_0.2.0.zip(r-4.5-any)
Usmile_0.2.0.tgz(r-4.6-any)Usmile_0.2.0.tgz(r-4.5-any)
Usmile_0.2.0.tar.gz(r-4.7-any)Usmile_0.2.0.tar.gz(r-4.6-any)
Usmile_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
Usmile/json (API)

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

Bug tracker:https://github.com/bbwieckowska/usmile/issues

Datasets:

On CRAN:

Conda:

3.00 score 3 scripts 260 downloads 10 exports 19 dependencies

Last updated from:ac0fe64bb4. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK117
source / vignettesOK189
linux-releaseOK109
macos-releaseOK170
macos-oldrelOK209
windows-develOK76
windows-releaseOK83
windows-oldrelOK106
wasm-releaseOK94

Exports:CLBplotPIWplotROCplotUSapply_calibratorUSbind_outUScalc_mdlUScalc_rawUSfit_calibratorUSplotUSprep_mdl

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecyclepROCR6RColorBrewerRcpprlangS7scalesvctrsviridisLitewithr