Nghiên cứu dự đoán phá sản của doanh nghiệp sử dụng kỹ thuật học máy và SMOTEWB
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Keywords:
bankruptcy prediction, machine learning, imbalanced data, SMOTEWBAbstract
In the context of modern economy, the ability to predict corporate bankruptcy is becoming increasingly important, playing a key role in supporting managers and investors in making decisions to minimize financial risks. To meet this need, the present study proposed a novel method, using a combination of machine learning techniques and data balancing strategies. The main goal is to improve the accuracy of corporate bankruptcy prediction. The study was conducted through steps including thorough data preprocessing and developing classification models, with a special focus on integrating machine learning models with the SMOTEWB data balancing method. The experimental results show that the proposed model not only achieves high accuracy but also has the potential for wide application in practice
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