determineCut: determine best Accuracy cuttoff

In quantable: Streamline Descriptive Analysis of Quantitative Data Matrices

Description

determine best Accuracy cuttoff

Usage

determineCut(cases, controls, plot = FALSE, scanstep = 0.01)

Arguments

cases	a factor of predicted classes
controls	a factor of classes to be used as the true results
plot	create plot of threasholds versus Accuracy
scanstep	step size for threshold estimation

Examples

library(pROC)
cases <- rnorm(100,-1,1.1)
controls <- rnorm(500,1,1.1)
cut <- determineCut(cases,controls)
makeROCplot(cases,controls,abline=cut)

quantable documentation built on May 2, 2019, 4:05 p.m.