A novel approach called Counterfactual Synthetic Minority Oversampling Technique (SMOTE) has been developed to tackle the persistent issue of imbalanced data in healthcare. Traditional models trained ...

Machine learning has revolutionised the field of classification in numerous domains, providing robust tools for categorising data into discrete classes. However, many practical applications, such as ...

When predicting financial distress, an imbalanced data set of company data may cause overfitting to the majority class and lead to bad performance of the classifiers. The problem of classification ...