Beyond the Lab: Informed decision-making strategy for resampling in pain assessment
In many real-world classification problems, datasets exhibit a skewed class distribution, known as class imbalance, where one class has significantly more samples than another. Machine learning models trained on imbalanced data tend to favor the class with more samples. This bias toward the majority class leads to poor classification performance on rare but important cases,…




