# How does Performance function classify predictions as positive or negative? Package:ROCR

I'm performing a logistic regression on my training data. I used the glm function to get the model m. Now using the below codes from this link, I calculated AUC

$test\$score<-predict(m,type = 'response',test)pred <- prediction(test\$score,test\$good_bad)perf <- performance(pred,"tpr","fpr")\$

where score is the dependent variable (0 or 1).
To score the tpr (True positive rate) and fpr (False positive rate), you have to classify the predicted probabilities into 1 or 0.
What is the cutoff used for that? how can we change it?

Could not find anything useful in this main documentation as well.