Package: RobustMetrics 0.1.1
RobustMetrics: Calculates Robust Performance Metrics for Imbalanced Classification Problems
Calculates robust Matthews Correlation Coefficient (MCC) and robust F-Beta Scores, as introduced by Holzmann and Klar (2024) <doi:10.48550/arXiv.2404.07661>. These performance metrics are designed for imbalanced classification problems. Plots the receiver operating characteristic curve (ROC curve) together with the recall / 1-precision curve.
Authors:
RobustMetrics_0.1.1.tar.gz
RobustMetrics_0.1.1.zip(r-4.7)RobustMetrics_0.1.1.zip(r-4.6)RobustMetrics_0.1.1.zip(r-4.5)
RobustMetrics_0.1.1.tgz(r-4.6-any)RobustMetrics_0.1.1.tgz(r-4.5-any)
RobustMetrics_0.1.1.tar.gz(r-4.7-any)RobustMetrics_0.1.1.tar.gz(r-4.6-any)
RobustMetrics_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
RobustMetrics/json (API)
| # Install 'RobustMetrics' in R: |
| install.packages('RobustMetrics', repos = c('https://bernhardklar.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bernhardklar/robustmetrics/issues
- rf.data - Example Random Forest Data
Last updated from:2ff8ec3d91. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 98 | ||
| source / vignettes | OK | 138 | ||
| linux-release-x86_64 | OK | 95 | ||
| macos-release-arm64 | OK | 75 | ||
| macos-oldrel-arm64 | OK | 68 | ||
| windows-devel | OK | 65 | ||
| windows-release | OK | 66 | ||
| windows-oldrel | OK | 56 | ||
| wasm-release | OK | 68 |
Exports:FScoreMCCrobFScorerobFScore2robMCCROC_curve
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| F-Beta Score | FScore |
| Matthews correlation coefficient | MCC |
| Example Random Forest Data | rf.data |
| Robust F-Beta Score | robFScore |
| General robust F-Beta Score | robFScore2 |
| Robust Matthews correlation coefficient | robMCC |
| ROC curve | ROC_curve |
