Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo
Many real-world data sets exhibit imbalanced class distributions in which almost all instances are assigned to one class and far fewer instances to a smaller, yet usually interesting class. Building classification models from such imbalanced data sets is a relatively new challenge in the machine lea...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
Penerbit UiTM
2014
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| Online Access: | https://ir.uitm.edu.my/id/eprint/13930/1/13930.pdf https://ir.uitm.edu.my/id/eprint/13930/ https://mjoc.uitm.edu.my/ |
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