Class Probability, Imbalanced Data, Data Science, Knime, Theory.
class is fairly represented in the training data. Therefore if the data are imbalanced, the performance of most standard learning algorithms will be compromised, because their purpose is to maximize the overall accuracy. For a dataset with 99% negative events and 1% positive events, a model could