Package: roccv 1.2
Ben Sherwood
roccv: ROC for Cross Validation Results
Cross validate large genetic data while specifying clinical variables that should always be in the model using the function cv(). An ROC plot from the cross validation data with AUC can be obtained using rocplot(), which also can be used to compare different models. Framework was built to handle genetic data, but works for any data.
Authors:
roccv_1.2.tar.gz
roccv_1.2.tar.gz(r-4.5-noble)roccv_1.2.tar.gz(r-4.4-noble)
roccv_1.2.tgz(r-4.4-emscripten)roccv_1.2.tgz(r-4.3-emscripten)
roccv.pdf |roccv.html✨
roccv/json (API)
NEWS
| # Install 'roccv' in R: |
| install.packages('roccv', 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:dfc67dca75. Checks:3 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 22 2025 |
| R-4.5-linux | OK | Mar 22 2025 |
| R-4.4-linux | OK | Mar 22 2025 |
Exports:cvfit_pred_foldrandomly_assignrocplot
Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixplyrpROCRcppRcppEigenshapesurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Cross validation results for a model | cv |
| Cross validation on fold i | fit_pred_fold |
| Assigns n samples into k groups | randomly_assign |
| roccv: A package for creating ROC plots on cross validated data | roccv-package roccv |
| Create ROC plot from cross validation results | rocplot |