Package: staccuracy 0.2.2
staccuracy: Standardized Accuracy and Other Model Performance Metrics
Standardized accuracy (staccuracy) is a framework for expressing accuracy scores such that 50% represents a reference level of performance and 100% is a perfect prediction. The 'staccuracy' package provides tools for creating staccuracy functions as well as some recommended staccuracy measures. It also provides functions for some classic performance metrics such as mean absolute error (MAE), root mean squared error (RMSE), and area under the receiver operating characteristic curve (AUCROC), as well as their winsorized versions when applicable.
Authors:
staccuracy_0.2.2.tar.gz
staccuracy_0.2.2.zip(r-4.7)staccuracy_0.2.2.zip(r-4.6)staccuracy_0.2.2.zip(r-4.5)
staccuracy_0.2.2.tgz(r-4.6-any)staccuracy_0.2.2.tgz(r-4.5-any)
staccuracy_0.2.2.tar.gz(r-4.7-any)staccuracy_0.2.2.tar.gz(r-4.6-any)
staccuracy_0.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
staccuracy/json (API)
NEWS
| # Install 'staccuracy' in R: |
| install.packages('staccuracy', repos = c('https://tripartio.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tripartio/staccuracy/issues
Pkgdown/docs site:https://tripartio.github.io
Last updated from:a112bf9df3. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 150 | ||
| source / vignettes | OK | 155 | ||
| linux-release-x86_64 | OK | 130 | ||
| macos-release-arm64 | OK | 208 | ||
| macos-oldrel-arm64 | OK | 154 | ||
| windows-devel | OK | 88 | ||
| windows-release | OK | 82 | ||
| windows-oldrel | OK | 75 | ||
| wasm-release | OK | 112 |
Exports:aucrocmadmaereg_aucrocrmsesa_diffsa_mae_madsa_rmse_sdsa_wmae_madsa_wrmse_sdstaccuracywin_maewin_rmsewinsorize
Dependencies:clicpp11dplyrgenericsgluelifecyclemagrittrpillarpkgconfigpurrrR6rlangstringistringrtibbletidyrtidyselectutf8vctrswithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Area under the ROC curve | aucroc |
| Regression error and deviation measures | mad mae rmse |
| Area under the ROC curve for regression target outcomes | reg_aucroc |
| Statistical tests for the differences between standardized accuracies (staccuracies) | sa_diff |
| Standardized accuracy (staccuracy) functions. | sa_mae_mad sa_rmse_sd sa_wmae_mad sa_wrmse_sd staccuracy |
| Winsorize a numeric vector | winsorize win_mae win_rmse |
