Class Probability, Imbalanced Data, Data Science, Knime, Theory.
classes (a priori distribution) of the training data in order to obtain a classifier that can effectively predict the minority class (the actual fraudulent transactions). Resampling techniques Undersampling. A random sample of events from the majority class is drawn and removed from the training