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: | Article |
| Language: | English |
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Trường Đại học Vinh
2024-09-01
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| Series: | Tạp chí Khoa học |
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| Online Access: | https://vujs.vn//api/view.aspx?cid=02ecfdc3-b816-4a0d-b2ae-30515a12ccbd |