How to Plot the ROC Curve in rStudios from the given values?

1
votes

Confusion Matrix Values

  1. Cut-off / TP / FP / TN / FN

  2. 0.1 100 50 500 450

  3. 0.2 150 100 450 400

  4. 0.3 250 150 400 300

  5. 0.4 300 200 350 250

  6. 0.5 350 250 300 200

  7. 0.6 350 300 250 200

  8. 0.7 400 350 200 150

  9. 0.8 400 400 150 150

  10. 0.9 450 450 100 100

  11. 1.0 500 500 50 50

2
rroc
Note that this is not actually a ROC curve, which should visit every possible threshold, not just 10. Depending on the context you may want to call it something else. – Calimo

2 Answers

3
votes

Using only base-R, you could write the following code:

## your data
df <- read.table(header = TRUE, text = "
Cut_off TP FP TN FN
0.1 100 50 500 450
0.2 150 100 450 400
0.3 250 150 400 300
0.4 300 200 350 250
0.5 350 250 300 200
0.6 350 300 250 200
0.7 400 350 200 150
0.8 400 400 150 150
0.9 450 450 100 100
1.0 500 500 50 50")

## calculate False Positive ratio
df$FPR <- df$FP/(df$FP + df$TN)
## calculte True Positive Ratio
df$TPR <- df$TP/(df$TP + df$FN)

## df is now: 
   Cut_off  TP  FP  TN  FN        FPR       TPR
      0.1 100  50 500 450 0.09090909 0.1818182
      0.2 150 100 450 400 0.18181818 0.2727273
      0.3 250 150 400 300 0.27272727 0.4545455
      0.4 300 200 350 250 0.36363636 0.5454545
      0.5 350 250 300 200 0.45454545 0.6363636
      0.6 350 300 250 200 0.54545455 0.6363636
      0.7 400 350 200 150 0.63636364 0.7272727
      0.8 400 400 150 150 0.72727273 0.7272727
      0.9 450 450 100 100 0.81818182 0.8181818
      1.0 500 500  50  50 0.90909091 0.9090909

## plot the ROC with base plot
plot(df$FPR, df$TPR, type = "b", 
     xlim = c(0,1), ylim = c(0,1), 
     main = 'ROC Curve',
     xlab = "False Positive Rate (1 - Specificity)",
     ylab = "True Positive Rate (Sensitivity)",
     col = "blue")
abline(a = 0, b = 1, lty=2, col = "grey") ### pure chance line

yielding the following plot:

enter image description here

if you want to mark the cut-off points with a label you need the following line after the line with abline(...

text(df$FPR, df$TPR+.05, df$Cut_off, col = "blue", cex = .7)

yielding this plot:

enter image description here

1
votes

Here is one way you can have a ROC plot with ggplot and dplyr. First here is your data:

df = structure(list(Cutoff = c(0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 
     0.8, 0.9, 1), TP = c(100, 150, 250, 300, 350, 350, 400, 400, 
     450, 500), FP = c(50, 100, 150, 200, 250, 300, 350, 400, 450, 
     500), TN = c(500, 450, 400, 350, 300, 250, 200, 150, 100, 50), 
     FN = c(450, 400, 300, 250, 200, 200, 150, 150, 100, 50)), class = 
     "data.frame", row.names = c(NA,-10L))

and for ROC, you need False-Positive-rate (FPR) and True-Positive-rate (TPR) which here I calculate with mutate: 

df %>% mutate( FPR = FP / (FP + TN) , TPR = TP / ( TP + FN )) %>%
   ggplot( aes ( x = FPR , y = TPR)) + geom_point(size = 0) + 
   geom_line(size = 1, alpha = 1) + theme_bw() +
   xlab("1 - Specificity") + ylab("Sensitivity") +
   theme(
     plot.title = element_text(size = 20,hjust = 0.5),
     axis.text = element_text(size =10),
     axis.title = element_text(size = 20)
   ) + annotate('segment' , x = 0, xend = 1, y = 0, yend = 1, alpha = 0.7)

And here is the result: enter image description here

If you want to have points on the plots you can change the size in geom_point and this would be the result: enter image description here