# R - ROCR Library - Understanding predict and prediction method

My name is Abhi and I am trying to understand the difference between predict and prediction.

I am using the r language and my ide is rstudio. I have created a random forest model (r package randomForest)

myModel <- randomForest(Survived ~ .,data = modelData[,-1],importance = T)
modelResponses = predict(model,type = "prob") # I am guessing this gives probability of survival for each passenger
temp1 = modelResponses[,2]
pred = prediction(temp1,trainData\$Survived) #Not Sure whats is the pred object


Now here are my questions

1. What is the pred object?
2. I have seen some code which uses the pred object to plot the auc curve. I know temp1 is the probability of survival for each record. Say the probability of survival for a particular record is 0.55. How does the prediction function know to classify this as survived or not-survived?
3. How do I use this model to classify new data. Until now I was using modelResponses = predict(model,type = "prob") , but now I am not so sure. Again the same confusion as item 2, how does the system determine the best cut off point for probabilities.

Thanks a lot guys. Any help would be much appreciated.

Regards,