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.
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:
- 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 curve);
- transforming the marker by a function either defined by the user or resulting from a logistic
regression model (hROC curve);
- considering a linear transformation with some fixed parameters introduced by the user,
dynamic parameters or empirically maximizing TPR for each FPR for a bivariate marker.
Also a quadratic transformation with particular coefficients or a function fitted by a logistic
regression model can be considered (biROC curve);
- considering a linear transformation with some fixed parameters introduced by the user,
dynamic parameters or a function fitted by a logistic regression model (multiROC curve).
The classification regions behind each point of the ROC curve are displayed in both fixed
graphics (plot.buildROC(), plot.regions() or plot.funregions() function) or videos (movieROC()
function).
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=movieROC
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.
[aut, cre]