movieROC: Visualizing the Decision Rules Underlying Binary Classification

Visualization of decision rules for binary classification and Receiver Operating Characteristic (ROC) curve estimation under different generalizations proposed in the literature: - making the classification subsets flexible to cover those scenarios where both extremes of the marker are associated with a higher risk of being positive, considering two thresholds (gROC() function); - transforming the marker by a proper function trying to improve the classification performance (hROC() function); - when dealing with multivariate markers, considering a proper transformation to univariate space trying to maximize the resulting AUC of the TPR for each FPR (multiROC() function). The classification regions behind each point of the ROC curve are displayed in both static graphics (plot_buildROC(), plot_regions() or plot_funregions() function) or videos (movieROC() function).

Version: 0.1.1
Depends: R (≥ 3.5.0)
Imports: rms, animation, intrval, gtools, e1071, robustbase, Rsolnp, ks, zoo
Suggests: R.rsp
Published: 2024-06-28
DOI: 10.32614/CRAN.package.movieROC
Author: Sonia Perez-Fernandez ORCID iD [aut, cre]
Maintainer: Sonia Perez-Fernandez <perezsonia at>
License: GPL-3
NeedsCompilation: no
CRAN checks: movieROC results


Reference manual: movieROC.pdf
Vignettes: movieROC vignette


Package source: movieROC_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): movieROC_0.1.1.tgz, r-oldrel (arm64): movieROC_0.1.1.tgz, r-release (x86_64): movieROC_0.1.1.tgz, r-oldrel (x86_64): movieROC_0.1.1.tgz
Old sources: movieROC archive


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