To address this issue, we present a quantitative approach, the Maximum Fractional Difference (MFD) method, which enables the evaluation of model performance for the task of training an OCC model to differentiate between negative and positive samples and thus predict the instances of an unknown dataset that are most likely to belong to the positive labelled class.