Abstract: Class imbalance is a pervasive challenge in real-world machine learning (ML) applications, where the minority class, often the class of interest, is significantly underrepresented. This ...
Our paper utilizes four datasets; however, for simplicity, we provide dataset preparation code only for the UNC 3T-7T paired dataset. Other datasets can be prepared using similar code with minor ...
Abstract: Multi-class imbalanced classification is a challenge in machine learning. The classical synthetic minority oversampling technique (SMOTE) alleviates this challenge by balancing the class ...
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