The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Ke, B. S., Chiang, A. J., & Chang, Y. C. I. (2018) <doi:10.1080/10543406.2017.1377728> provide two theoretical methods (influence function and local influence) based on the area under the receiver operating characteristic curve (AUC) to quantify the numerical impact of each observation to the overall AUC. Alternative graphical tools, cumulative lift charts, are proposed to reveal the existences and approximate locations of those influential observations through data visualization.
| Version: | 0.1.2 |
| Imports: | dplyr, geigen, ggplot2, ggrepel, methods, ROCR |
| Published: | 2020-05-30 |
| DOI: | 10.32614/CRAN.package.influenceAUC |
| Author: | Bo-Shiang Ke [cre, aut, cph], Yuan-chin Ivan Chang [aut], Wen-Ting Wang [aut] |
| Maintainer: | Bo-Shiang Ke <naivete0907 at gmail.com> |
| BugReports: | https://github.com/BoShiangKe/InfluenceAUC/issues |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | influenceAUC results |
| Reference manual: | influenceAUC.pdf |
| Package source: | influenceAUC_0.1.2.tar.gz |
| Windows binaries: | r-devel: influenceAUC_0.1.2.zip, r-release: influenceAUC_0.1.2.zip, r-oldrel: influenceAUC_0.1.2.zip |
| macOS binaries: | r-release (arm64): influenceAUC_0.1.2.tgz, r-oldrel (arm64): influenceAUC_0.1.2.tgz, r-release (x86_64): influenceAUC_0.1.2.tgz, r-oldrel (x86_64): influenceAUC_0.1.2.tgz |
| Old sources: | influenceAUC archive |
Please use the canonical form https://CRAN.R-project.org/package=influenceAUC to link to this page.
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.
Health stats visible at Monitor.