DBSMOTE: Density-based synthetic minority over-sampling technique
A dataset exhibits the class imbalance problem when a target class has a very small number of instances relative to other classes. A trivial classifier typically fails to detect a minority class due to its extremely low incidence rate. In this paper, a new over-sampling technique called DBSMOTE is p...
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| Main Authors: | , , |
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| 格式: | Article |
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Springer Netherlands
2015
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| 主題: | |
| 在線閱讀: | http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84862140885&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/38631 |
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| 機構: | Chiang Mai University |