The artificial intelligence community has long struggled with a fundamental challenge of making AI systems transparent and ...

Imbalanced datasets are prevalent in real life. The imbalanced datasets pose challenges for classification and regression tasks. Compared to imbalanced classification, imbalanced regression deals with ...

Aimming at the ever-present problem of imbalanced data in text classification, the authors study on several forms of imbalanced data, such as text number, class size, subclass and class fold. Some ...

Based on my research, metrics like AUC, Balanced Accuracy, and F1-score are often recommended for evaluating model performance when dealing with imbalanced sample groups. However, when I attempt to ...