1. At least one computer program provided on at least one non-transitory computer readable storage medium and comprising code that when executed causes at least one computer to perform a method comprising: training a machine learning classifier with a set of labeled training data, such that the trained classifier is operable to determine a score with respect to the classification of cases for a category; determining at least one first distribution of scores for positive cases in the training set, wherein a positive case is a case that belongs to the category; determining at least one second distribution of scores for negative cases in the training set, wherein a negative case is a case that does not belong to the category; determining a third distribution of scores generated by the classifier classifying cases in a set of target data; and estimating a proportion of cases in the target set that are positive cases by fitting the at least one first distribution and the at least one second distribution to the third distribution.