1. 不平衡数据集分类方法研究综述.
- Author
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周 玉, 孙红玉, 房 倩, and 夏 浩
- Subjects
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MACHINE learning , *PROBLEM solving , *SAMPLING methods , *CLASSIFICATION algorithms , *ELECTRONIC data processing , *ALGORITHMS - Abstract
The development of society has brought countless data, with the unbalancedness becoming a significant feature of many data sets. So it has come to be a research hotspot for machine learning on how to make those unbalanced data sets obtain better effects of classification. Based on this, this paper conducted a comprehensive research on the current unbalanced data set classification method, and made an overall interpretation and conclusion from such three aspects as the unbalanced data sampling method, the method of machine learning-based improved algorithm and the combination method. It also analyzed and took int o account many factors, including the problems solved by each method, algorithm mentality, application scenarios, as well as the advantages and disadvantages of each, and delivered a summary on potential problems of the classification methods and a prospect on the future research directions [ABSTRACT FROM AUTHOR]
- Published
- 2022
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