如何从给定的值 Plot rStudios 中的 ROC 曲线？

Question

混淆矩阵值

1. 截止 / 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

Answer 1

仅使用 base-R，您可以编写以下代码：

## 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

产生以下 plot：

如果你想用 label 标记截止点，你需要在abline(...

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

产生这个 plot：

Answer 2

这是您可以使用带有ggplot和dplyr的 ROC plot 的一种方法。 首先是您的数据：

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))

对于 ROC，您需要 False-Positive-rate (FPR) 和 True-Positive-rate (TPR)，我在这里使用mutate计算：

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) 

结果如下：

如果你想在图上有点，你可以改变geom_point的大小，这将是结果：