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 of 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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