's data, where critical outcomes tend to be inherently rare. To address this challenge, we propose a novel oversampling … approach, the counterfactual synthetic minority oversampling technique (Counterfactual SMOTE), which combines SMOTE with a … counterfactual generation framework. Our method intrinsically performs an oversampling process near the decision boundary within a …

resampling strategy integrated with random over-sampling examples and Tomek link. The developed resampling strategy increases …

Coarsened Exact Matching (CEM) method in conjunction with the Synthetic Minority Oversampling Technique (SMOTE), our analysis …

using a genetic-based oversampling technique. To evaluate the performance of ReCO-BGA, we conducted several experiments …

, demonstrating their superior performance over traditional statistical models. Addressing class imbalance through oversampling … techniques such as the synthetic minority oversampling technique (SMOTE), the paper achieves higher accuracy rates with AI …

, demonstrating their superior performance over traditional statistical models. Addressing class imbalance through oversampling … techniques such as the synthetic minority oversampling technique (SMOTE), the paper achieves higher accuracy rates with AI …

problem, random oversampling was applied. This study also utilized the BiLSTM model to recognize each entity in new textual … by NER. Oversampling ensured that the proposed NER model could precisely recognize all entities and reduce biased results …

-poor classes, an oversampling technique was employed. Imbalanced data affect classification, particularly when predicting the … results of the classification. The following oversampling techniques were employed in this study: Random Oversampling (RO …), the Adaptive Synthetic (ADASYN) and the Synthetic Minority Oversampling Technique (SMOTE). It was found that, of the three …