Package: Metrics 0.1.4
Metrics: Evaluation Metrics for Machine Learning
An implementation of evaluation metrics in R that are commonly used in supervised machine learning. It implements metrics for regression, time series, binary classification, classification, and information retrieval problems. It has zero dependencies and a consistent, simple interface for all functions.
Authors:
Metrics_0.1.4.tar.gz
Metrics_0.1.4.zip(r-4.5)Metrics_0.1.4.zip(r-4.4)Metrics_0.1.4.zip(r-4.3)
Metrics_0.1.4.tgz(r-4.4-any)Metrics_0.1.4.tgz(r-4.3-any)
Metrics_0.1.4.tar.gz(r-4.5-noble)Metrics_0.1.4.tar.gz(r-4.4-noble)
Metrics_0.1.4.tgz(r-4.4-emscripten)Metrics_0.1.4.tgz(r-4.3-emscripten)
Metrics.pdf |Metrics.html✨
Metrics/json (API)
| # Install 'Metrics' in R: |
| install.packages('Metrics', repos = c('https://mfrasco.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mfrasco/metrics/issues
Last updated 5 years agofrom:ca12765d3e. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 10 2024 |
| R-4.5-win | OK | Sep 10 2024 |
| R-4.5-linux | OK | Sep 10 2024 |
| R-4.4-win | OK | Sep 10 2024 |
| R-4.4-mac | OK | Sep 10 2024 |
| R-4.3-win | OK | Sep 10 2024 |
| R-4.3-mac | OK | Sep 10 2024 |
Exports:accuracyaeapeapkaucbiasceexplained_variationf1fbeta_scorelllogLossmaemapemapkmasemdaeMeanQuadraticWeightedKappamsemslepercent_biasprecisionraerecallrmsermslerrserseScoreQuadraticWeightedKappaseslesmapesse
Dependencies:
