BestCut: Best Cutpoint for a ROC Curve

In ModTools: Building Regression and Classification Models

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 "youden" or "closest.topleft", controls how the optimal threshold is determined. See details.

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 <[e-mail]>, Andri Signorell <[e-mail]> (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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1186/1471-2105-12-77")}.

See Also

ROC

Examples

r.glm <- FitMod(diabetes ~ ., data = d.pima, fitfn="logit")

ROC(r.glm)
BestCut(ROC(r.glm))

ModTools documentation built on Sept. 30, 2024, 9:12 a.m.