visualize.roc.curve: Plot Roc curve

In AnderEhu/sme:

Description

Plot Roc curve

Usage

visualize.roc.curve(roc.FPR, roc.TPR, auc, file = "None")

Arguments

roc.FPR	a numerical vector representing false positive rates
roc.TPR	a numerical vector representing true positive rates
auc	auc value. Use auc() function.
file	name of output file for saving roc curve plot.

Value

Plot roc curve

Examples

random.x <- sample.int(3000,1000,replace=FALSE)
class <- c(rep(TRUE, 500), rep(FALSE, 500))
pos <- sample.int(1000, 1000)
random.y <- class[order(pos)]
roc.curve <- roc.curve(random.x, random.y)
auc <- auc(roc.curve$FPR , roc.curve$TPR )
visualize.roc.curve(roc.curve$FPR , roc.curve$TPR, auc)
visualize.roc.curve(roc.curve$FPR , roc.curve$TPR, auc, file = "randomRocCurve")

AnderEhu/sme documentation built on Jan. 31, 2022, 12:01 a.m.