HIGHLIGHTS
- What: This study evaluates the effectiveness of various such as class weights random under-sampling SMOTE and SMOTEENN multiple machine learning models namely XGBoost Random Forest CNN BIGRU BILSTM CNN-LSTM and CNN-BIGRU to address the critical challenge of dataset imbalance in Accuracy AUC precision recall and F1-score were used to evaluate the performance of these models on balanced and imbalanced datasets. This study shows how data balancing techniques can Aljohani: Enhancing Arabic Fake News Detection: Evaluating Data Balancing Techniques Across … significantly enhance the performance of machine_learning models.
- Who: gerry from the Department . . .
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