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High-level scheme of hyperSMURF. Step 1: partitioning of the training set (the minority/positive class is represented in blue, while the majority/negative class is in green). Step 2: application of oversampling and undersampling approaches, and assembling of the training set. Step 3: training of the random forest models. Step 4: testing and aggregation of prediction outcomes.
