Class Probability, Imbalanced Data, Data Science, Knime, Theory.
Figure 1: Workflow that compares three ways of training and applying a classification model using imbalanced data. Firstly, the model training is done on imbalanced data. Secondly, the training set is resampled using SMOTE to make it balanced. Thirdly, the training set is resampled using SMOTE and