Class Probability, Imbalanced Data, Data Science, Knime, Theory.
cost as obtained by a fraud detection model that was trained on an oversampled, balanced data, and where the predicted class probabilities were corrected according to the a priori class distribution. As the results for this scenario in Table 4 show, correcting the predicted class probabilities