| DOI | Resolve DOI: https://doi.org/10.1109/DSAA53316.2021.9564135 |
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| Author | Search for: Koziarski, Michal; Search for: Bellinger, Colin1; Search for: Wozniak, Michal |
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| Affiliation | - National Research Council Canada. Digital Technologies
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| Format | Text, Article |
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| Conference | 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA), October 6-9, 2021, Porto, Portugal |
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| Subject | imbalanced data; voversampling; radial basis functions |
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| Abstract | In this paper we propose Radial-Based Combined Cleaning and Resampling (RB-CCR) algorithm. RB-CCR utilizes the concept of class potential to refine the energy-based resampling approach of previously proposed CCR algorithm. In particular, RB-CCR exploits the class potential to accurately locate sub-regions of the data-space for synthetic oversampling. The category sub-region for oversampling can be specified as an input parameter to meet domain-specific needs or be automatically selected via cross-validation. The results of the conducted experimental study show that RB-CCR achieves a better precision-recall trade-off than CCR and generally outperforms the state-of-the-art resampling methods in terms of AUC and G-mean. |
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| Publication date | 2021-10-06 |
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| Publisher | IEEE |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | c4cb8938-38ff-47ae-ae68-45f0bf675014 |
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| Record created | 2022-02-01 |
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| Record modified | 2022-02-01 |
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