Class Probability, Imbalanced Data, Data Science, Knime, Theory.
setup leads to biased values for the predicted class probabilities, because the training set does not represent the test set or any new, unseen data. Therefore, to obtain an optimal performance of a classification model together with reliable classification results, correcting the predicted class