> install.packages("pROC")
> library(pROC)
> result <- read.csv("model_result.csv", header=TRUE)
> (m_roc <- roc(result$SIU_CUST_YN, result$predicted_yn))

Call:
roc.default(response = result$SIU_CUST_YN, predictor = result$predicted_yn)

Data: result$predicted_yn in 1635 controls (result$SIU_CUST_YN 0) < 158 cases (result$SIU_CUST_YN 1).
Area under the curve: 0.7369
> plot.roc(m_roc, col="red",   # 선의 색상을 설정합니다.
+          print.auc=TRUE, print.auc.adj=c(2.5,-8),    # auc 값 출력
+          max.auc.polygon=TRUE,   # auc의 최대 면적 출력
+          print.thres=TRUE, print.thres.pch=19, print.thres.col = "red", 
+          print.thres.adj=c(0.3,-1.2), # 기준치(cut-off value) 설정
+          auc.polygon=TRUE, auc.polygon.col="#D1F2EB")