ROC/Confusion matrix

### Example online
# Load library
library(pROC)

### Actual outcomes
outcomes <- c(rep(0,27),(rep(1,76)))

# Set seed
set.seed(42)

### Prediction Method 1
pred1 <- c(rep(0,4),(rep(1,99)))

### Prediction Method 2
pred2 <- c(rnorm(27,mean=0.3, sd=0.2),rnorm(76,mean=0.5, sd=0.2))

# Compare ROC
roc1 <- roc(outcomes,pred1)
roc2 <- roc(outcomes,pred2)
plot(roc1, print.auc=F, lty=2, xlim=c(1,0), lwd=3)
text(0.15, 0.1, labels=sprintf("Method1|AUC: %0.3f", auc(roc1)), col="black")
lines(roc2, col="green", lty=4, lwd=3)
text(0.15, 0.05, labels=sprintf("Metod2|AUC: %0.3f", auc(roc2)), col="green")

# Compare confusion matrices
confusionMatrix(factor(outcomes),factor(pred1))
confusionMatrix(factor(outcomes),factor((pred2>=0.35)*1))