I have implemented a classifier and I can calculate the precision and recall when testing the classifier (two classes) in the test set(>100). Is it meaningful to talk about the confidence interval for the precision(recall)? The precision(recall) can be defined as a random variable. I assume that my sample is the test set and there is a precision related to it with the defined classifier. How should I define the distribution for the precision for class 1 (#of correct classifications of c1 / #of total classifications of c1)? One alternative is to use the Binomial distribution for proportions.