DET (version 3.0.0)

pointsEER: EER Plot

Description

From a 'DETs' object, this function plots the EER points of each classifier within the same graph of the DETs curves.

Usage

pointsEER(
  dets,
  pch = 19,
  col = c("black", "blue", "red", "green", "yellow"),
  lwd = 3,
  ...
)

Arguments

dets

An object of class "DETs".

pch

Symbol used for plotting the EER points, by default pch = 19.

col

A vector of colors, specifying the color of the points for each DET curve.

lwd

Line width used for drawing symbols, by default lwd = 3.

...

Further graphical arguments passed to the points function. For example, by default pch = 19 and lwd = 3 (see points, for more details).

Examples

# NOT RUN {
library(DET)
n = 5000
#Predictors with normal distribution
set.seed(1235)
scoreNegative1 = rnorm(n, mean = 0.25, sd = 0.125)
set.seed(5321)
scoreNegative2 = rnorm(n, mean = 0.25, sd = 0.125)
set.seed(6987)
scoreNegative3 = rnorm(n, mean = 0.25, sd = 0.125)
set.seed(11452)
scorePositive1 = rnorm(n, mean = 0.55, sd = 0.125)
set.seed(54321)
scorePositive2 = rnorm(n, mean = 0.65, sd = 0.125)
set.seed(65987)
scorePositive3 = rnorm(n, mean = 0.75, sd = 0.125)
response = as.factor(c(rep(c("target"), times = n), rep(c("nontarget"), times = n)))
predictor1 = c(scoreNegative1, scorePositive1)
predictor2 = c(scoreNegative2, scorePositive2)
predictor3 = c(scoreNegative3, scorePositive3)
predictors = matrix(c(predictor1, predictor2, predictor3), ncol = 3)
colnames(predictors) = c("DET1", "DET2", "DET3")
detCurves = detc(
  response,
  predictors,
  positive = "target",
  names = colnames(predictors),
  plot = TRUE,
  main = "Example",
  col = c("black", "blue", "red"))

pointsEER(detCurves)
# }