roc_plot: Receiver Operating Characteristic curve

In Rkabacoff/qacr: Functions to Facilitate Data Science Projects

Description

Plot a receiver operating characteristic curve for a binary predictive model

Usage

roc_plot(actual, prob, positive, n.cuts = 20, labelsize = 3, labelround = 2)

Arguments

actual	actual class.
prob	predicted probability for the target class
positive	label for the target class
n.cuts	number of probability cut-points to plot
labelsize	size of cutpoint labels
labelround	number of decimal digits in the cutpoint labels

Value

a ggplot2 graph

Examples

# logistic regression
data(heart)
heart <- na.omit(heart)
fit <- glm(disease ~ . , heart, family=binomial)
prob <- predict(fit, newdata=heart, type="response")
roc_plot(heart$disease, prob, positive="yes")

Rkabacoff/qacr documentation built on March 20, 2021, 3:03 p.m.