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Sensitivity (or recall or true positive rate), false positive rate, specificity, precision (or positive predictive value), negative predictive value, misclassification rate, accuracy, F-score- these are popular metrics for assessing performance of binary classifier for certain threshold. These metrics are calculated at certain threshold values. Receiver operating characteristic (ROC) curve is a common tool for assessing overall diagnostic ability of the binary classifier. Unlike depending on a certain threshold, area under ROC curve (also known as AUC), is a summary statistic about how well a binary classifier performs overall for the classification task. ROCit package provides flexibility to easily evaluate threshold-bound metrics. Also, ROC curve, along with AUC, can be obtained using different methods, such as empirical, binormal and non-parametric. ROCit encompasses a wide variety of methods for constructing confidence interval of ROC curve and AUC. ROCit also features the option of constructing empirical gains table, which is a handy tool for direct marketing. The package offers options for commonly used visualization, such as, ROC curve, KS plot, lift plot. Along with in-built default graphics setting, there are rooms for manual tweak by providing the necessary values as function arguments. ROCit is a powerful tool offering a range of things, yet it is very easy to use.
Version: | 2.1.2 |
Imports: | stats, graphics, utils, methods |
Suggests: | testthat, knitr, rmarkdown |
Published: | 2024-05-16 |
DOI: | 10.32614/CRAN.package.ROCit |
Author: | Md Riaz Ahmed Khan [aut, cre], Thomas Brandenburger [aut] |
Maintainer: | Md Riaz Ahmed Khan <mdriazahmed.khan at jacks.sdstate.edu> |
License: | GPL-3 |
NeedsCompilation: | no |
Language: | en-US |
Materials: | README NEWS |
CRAN checks: | ROCit results |
Reference manual: | ROCit.pdf |
Vignettes: |
ROCit: An R Package for Performance Assessment of Binary Classifier with Visualization |
Package source: | ROCit_2.1.2.tar.gz |
Windows binaries: | r-devel: ROCit_2.1.2.zip, r-release: ROCit_2.1.2.zip, r-oldrel: ROCit_2.1.2.zip |
macOS binaries: | r-release (arm64): ROCit_2.1.2.tgz, r-oldrel (arm64): ROCit_2.1.2.tgz, r-release (x86_64): ROCit_2.1.2.tgz, r-oldrel (x86_64): ROCit_2.1.2.tgz |
Old sources: | ROCit archive |
Reverse imports: | adjROC, animalcules, cutoff, itsdm, Rprofet, TBSignatureProfiler |
Reverse suggests: | DataVisualizations |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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