NÂNG CAO ĐỘ CHÍNH XÁC PHÂN LOẠI LỚP ÍT MẪU TỪ TẬP DỮ LIỆU MẤT CÂN BẰNG
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A dataset is called imbalance if it has some classes containing more instances than others. In this case, accurately classifying samples in small classes is very difficult. The higher the imbalanced ratio, the more difficult getting a good solution. Cost-sensitive learning is an effective solution for the imbalanced problem. In this paper, we present a decision system with misclassification cost. The system improves the degree of precision in the minor classes which are interested in imbalanced dataset.The system is based on the study of methods of classifying on the imbalanced dataset by cost-sensitive. This system is applied in medical diagnostic. The experimental results show that the accuracy of the diagnostic system is improved.
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