library(pROC)
d<- data.frame(Titanic)
d$Survived <- ifelse(d$Survived == "No", 0,1)
m<- glm(Survived ~ Class+Sex+Age+Freq, data=d, family = binomial(link = "logit"))
fitted.results <- predict(m,newdata=subset(d,select=c(1,2,3,5)),type='response')
auc(d$Survived, fitted.results)


### unbalancing the data by converting y to 1 where freq is even( just a random condition)

d$Survived_unbalanced <-ifelse(d$Freq %% 2 == 0,1,d$Survived)
m_ub<- glm(Survived_unbalanced ~ Class+Sex+Age+Freq, data=d, family = binomial(link = "logit"))
fitted.results_ub <- predict(m_ub,newdata=subset(d,select=c(1,2,3,5)),type='response')
auc(d$Survived_unbalanced, fitted.results_ub)