Package: hmeasure 1.0-2
Christoforos Anagnostopoulos
hmeasure: The H-Measure and Other Scalar Classification Performance Metrics
Classification performance metrics that are derived from the ROC curve of a classifier. The package includes the H-measure performance metric as described in <http://link.springer.com/article/10.1007/s10994-009-5119-5>, which computes the minimum total misclassification cost, integrating over any uncertainty about the relative misclassification costs, as per a user-defined prior. It also offers a one-stop-shop for other scalar metrics of performance, including sensitivity, specificity and many others, and also offers plotting tools for ROC curves and related statistics.
Authors:
hmeasure_1.0-2.tar.gz
hmeasure_1.0-2.tar.gz(r-4.5-noble)hmeasure_1.0-2.tar.gz(r-4.4-noble)
hmeasure_1.0-2.tgz(r-4.4-emscripten)hmeasure_1.0-2.tgz(r-4.3-emscripten)
hmeasure.pdf |hmeasure.html✨
hmeasure/json (API)
NEWS
| # Install 'hmeasure' in R: |
| install.packages('hmeasure', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:c43023f41f. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 01 2024 |
| R-4.5-linux | OK | Nov 01 2024 |
Exports:HMeasuremisclassCountsplotROCrelabel
Dependencies:
