recall.at.prec: Calculate maximum recall at given minimum precision

In jweile/yogiroc: Draw ROC and PRC curves

Calculate maximum recall at given minimum precision

Description

Calculate maximum recall at given minimum precision

Usage

recall.at.prec(yr2, x = 0.9, monotonized = TRUE, balanced = FALSE)

Arguments

yr2	the yogiroc2 object
x	the precision cutoff (default 0.9)
monotonized	whether or not to use monotonized PRC
balanced	whether or not to use prior-balancing

Examples

#generate fake data
truth <- c(rep(TRUE,10),rep(FALSE,8))
scores <- cbind(
  pred1=c(rnorm(10,1,0.2),rnorm(8,.9,0.1)),
  pred2=c(rnorm(10,1.1,0.2),rnorm(8,.9,0.2))
)
#create yogiroc2 object
yrobj <- yr2(truth,scores)
#calculate R90P
recall.at.prec(yrobj)
#calculate non-monotonized R90P
recall.at.prec(yrobj,monotonized=FALSE)
#calculate balanced R90P
recall.at.prec(yrobj,balanced=TRUE)

jweile/yogiroc documentation built on Jan. 15, 2024, 2:47 a.m.