1. A method for computing a classification threshold for a classifier, the method comprising: applying a classification model to a data item stored in a memory and having a known classification to produce a first classification score for the data item; determining a first classification of the data item based on the first classification score; determining an amount of retraining needed to change the first classification of the data item to a second, different classification; determining a reliability measure based on the amount of retraining needed to change the first classification of the data item to a second, different classification; modifying the first classification score based on the reliability measure to compute a second classification score; computing, using a processor, a threshold value that minimizes misclassification costs based, at least in part, on the second classification score and the known classification; and setting the classification threshold to the determined threshold value.