IMPROVING PERFORMANCE FOR IMBALANCED DATA CLASSIFICATION USING OVERSAMPLING AND CHARACTERISTICS OF EACH CLUSTER
This paper proposes a method to enhance the effectiveness of classifying imbalanced data. The main contribution of the method is integrating the K-means clustering algorithm and the minority oversampling technique VCIR to generate synthetic samples that closely represent the actual data characterist...
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| Format: | Artigo |
| Sprog: | Inglês |
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Trường Đại học Vinh
2024-09-01
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| Serier: | Tạp chí Khoa học |
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