url="http://freakonometrics.free.fr/german_credit.csv"
credit=read.csv(url, header = TRUE, sep = ",")

str(credit)

F=c(1,2,4,5,7,8,9,10,11,12,13,15,16,17,18,19,20)
for(i in F) credit[,i]=as.factor(credit[,i])

i_test=sample(1:nrow(credit),size=333)
i_calibration=(1:nrow(credit))[-i_test]

LogisticModel <- glm(Creditability ~ .,
                       family=binomial,
                      data = credit[i_calibration,])
summary(LogisticModel)


install.packages("ROCR")
library(ROCR)

fitLog <- predict(LogisticModel,type="response",   newdata=credit[i_test,])
pred = prediction( fitLog, credit$Creditability[i_test])
perf <- performance(pred, "tpr", "fpr")
plot(perf)
AUCLog2=performance(pred, measure = "auc")@y.values[[1]]
cat("AUC: ",AUCLog2,"\n")

install.packages("randomForest")
library(randomForest)
RF <- randomForest(Creditability ~ .,
                      data = credit[i_calibration,])
fitForet <- predict(RF,
                                           newdata=credit[i_test,],
                                           type="prob")[,2]
pred = prediction( fitForet, credit$Creditability[i_test])
perf <- performance(pred, "tpr", "fpr")
plot(perf)
AUCRF=performance(pred, measure = "auc")@y.values[[1]]
cat("AUC: ",AUCRF,"\n")