I am reading a book about classification systems. They tell me that Bagging is a technique where "we perform sampling with replacement, building the classifier on each bootstrap sample. Each sample has probability $1-(1/N)^N$ of being selected."
What could they mean by this? Probably this is quite easy but somehow I do not get it. N is the number of classifier combinations (=samples), right? Why is the formula given above right? Why isn't the probability of a sample being selected simply $1/N$?