ML-ROS (see Algorithm 1) uses the IRLbl metric to find minority labels (i.e., IRLbl > MeanIR). It randomly selects instances from these minority labels to clone. The algorithm constantly updates IRLbl during each cycle, so if a minority label crosses MeanIR, it stops being cloned. It's crucial to remember that non-minority labels could also be present in cloned instances, which could increase the frequency of these labels in the dataset.