Package: evabic 0.1.1
Antoine Bichat
evabic: Evaluation of Binary Classifiers
Evaluates the performance of binary classifiers. Computes confusion measures (TP, TN, FP, FN), derived measures (TPR, FDR, accuracy, F1, DOR, ..), and area under the curve. Outputs are well suited for nested dataframes.
Authors:
evabic_0.1.1.tar.gz
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evabic.pdf |evabic.html✨
evabic/json (API)
NEWS
| # Install 'evabic' in R: |
| install.packages('evabic', repos = c('https://abichat.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/abichat/evabic/issues
classifiermeasurespredictorsroc-curvestatistics
Last updated 2 years agofrom:128b2ee5a5. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 09 2024 |
| R-4.5-win | OK | Sep 09 2024 |
| R-4.5-linux | OK | Sep 09 2024 |
| R-4.4-win | OK | Sep 09 2024 |
| R-4.4-mac | OK | Sep 09 2024 |
| R-4.3-win | OK | Sep 09 2024 |
| R-4.3-mac | OK | Sep 09 2024 |
Exports:add_namesebc_ACCebc_allmeasuresebc_AUCebc_AUC_from_measuresebc_BACCebc_confusionebc_DORebc_F1ebc_FDRebc_FNebc_FNRebc_FORebc_FPebc_FPRebc_NLRebc_NPVebc_PLRebc_PPVebc_tidyebc_tidy_by_thresholdebc_TNebc_TNRebc_TPebc_TPR
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Add names to a vector | add_names |
| Available measures | ebc_allmeasures |
| Area under the curve | ebc_AUC ebc_AUC_from_measures |
| Confusion matrix | ebc_confusion |
| Tidy output for measures | ebc_tidy |
| Measures by threshold | ebc_tidy_by_threshold |
| Confusion measures. | ebc_FN ebc_FP ebc_TN ebc_TP |
| Derived measures. | ebc_ACC ebc_BACC ebc_DOR ebc_F1 ebc_FDR ebc_FNR ebc_FOR ebc_FPR ebc_NLR ebc_NPV ebc_PLR ebc_PPV ebc_TNR ebc_TPR |