Four Oversampling and Undersampling Methods for Imbalanced Datasets
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Oversampling and under-sampling are the techniques for imbalanced modeling datasets. We will compare four methods with the baseline random forest model results. They are Random Oversampling, SMOTE, Random Under-Sampling, and Near Miss Under-Sampling.