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ROCit  

Performance Assessment of Binary Classifier with Visualization
View on CRAN: Click here


Download and install ROCit package within the R console
Install from CRAN:
install.packages("ROCit")

Install from Github:
library("remotes")
install_github("cran/ROCit")

Install by package version:
library("remotes")
install_version("ROCit", "2.1.2")



Attach the package and use:
library("ROCit")
Maintained by
Md Riaz Ahmed Khan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-01-31
Latest Update: 2024-05-16
Description:
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.
How to cite:
Md Riaz Ahmed Khan (2019). ROCit: Performance Assessment of Binary Classifier with Visualization. R package version 2.1.2, https://cran.r-project.org/web/packages/ROCit. Accessed 08 Mar. 2026.
Previous versions and publish date:
1.1.1 (2019-01-31 00:23), 2.1.1 (2020-06-14 12:20)
Other packages that cited ROCit R package
View ROCit citation profile
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Complete documentation for ROCit
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