| BestCut {ModTools} | R Documentation |
Best Cutpoint for a ROC Curve
Description
Returns the best cutpoint for a given classification model.
Usage
BestCut(x, method = c("youden", "closest.topleft"))
Arguments
x |
a roc object from the roc function |
method |
one of |
Details
The method argument controls how the
optimal threshold is determined.
- '
youden' -
Youden's J statistic (Youden, 1950) is employed. The optimal cut-off is the threshold that maximizes the distance to the identity (diagonal) line. Can be shortened to “y”.
The optimality criterion is:
max(sensitivities + specificities) - '
closest.topleft' -
The optimal threshold is the point closest to the top-left part of the plot with perfect sensitivity or specificity. Can be shortened to “c” or “t”.
The optimality criterion is:
min((1 - sensitivities)^2 + (1- specificities)^2)
Value
the threshold value
Author(s)
Robin Xavier <pROC-cran@xavier.robin.name>, Andri Signorell <andri@signorell.net> (interface)
References
Xavier Robin, Natacha Turck, Alexandre Hainard, et al. (2011) “pROC: an open-source package for R and S+ to analyze and compare ROC curves”. BMC Bioinformatics, 7, 77. doi:10.1186/1471-2105-12-77.
See Also
Examples
r.glm <- FitMod(diabetes ~ ., data = d.pima, fitfn="logit")
ROC(r.glm)
BestCut(ROC(r.glm))