# 如何从给定值绘制rStudios中的ROC曲线？

1. 截止/ TP / FP / TN / FN
2. 0.1 100 50 500 450
3. 0.2150100450400
4. 0.3250150400300
5. 0.4300200350250
6. 0.5350250300200
7. 0.6 350300250200
8. 0.7 400 350200150
9. 0.8 400 400 150 150
10. 0.9450450100100
11. 1.0 500 500 50 50

• Oswal 回复

仅使用base-R，您可以编写以下代码：

``````## your data
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
``````

产生以下图：

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, seq(from =.1, to = 1, by = .1), col = "blue", cex = .7)
``````

产生这个情节：

• 泪眸人 回复

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:

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