R/plotMeanROC.R

In komorowskilab/R.ROSETTA: R.ROSETTA: an interpretable machine learning framework

plotMeanROC <- function(out, col="orangered3", backCol="snow2"){
  
  ROCstats <- out$ROCstats
  
  if(is.null(ROCstats)){
  ROCstats <- out$ROC.stats  
  }
  
  OMSpec <- rowMeans(unstack(ROCstats, form = OneMinusSpecificity ~ CVNumber))
  Sens <- rowMeans(unstack(ROCstats, form = Sensitivity ~ CVNumber))
  
  ## plotting with new colours
  plot(OMSpec, Sens, type = "l", lwd=3, col=col, xlab="1 - specificity (FPR)", ylab="sensitivity (TPR)", axes=F, cex.lab=1.5)
  polygon(c(1,OMSpec), c(0,Sens), lwd=0.01, col=backCol)
  text(0.75, 0.1, col=col, paste0("mean AUC = ",round(out$quality$ROC.AUC.MEAN, digits = 2)),cex = 1.5)
  axis(side=1, at=seq(0,1,0.1))
  axis(side=2, at=seq(0,1,0.1))
  
}