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Borderline Over-sampling for Imbalanced Data Classification
https://hiroshima.repo.nii.ac.jp/records/2000823
https://hiroshima.repo.nii.ac.jp/records/2000823b6428e79-02b9-4b1d-ac38-4b5cfd745a76
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
A1005.pdf (390.6 KB)
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| Item type | デフォルトアイテムタイプ_（フル）(1) | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2023-03-18 | |||||||||||
| タイトル | ||||||||||||
| タイトル | Borderline Over-sampling for Imbalanced Data Classification | |||||||||||
| 言語 | en | |||||||||||
| 作成者 |
Nguyen, Hien M.
× Nguyen, Hien M.
× Cooper, Eric W.
× Kamei, Katsuari
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| アクセス権 | ||||||||||||
| アクセス権 | open access | |||||||||||
| アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||||||||
| 権利情報 | ||||||||||||
| 権利情報 | (c) Copyright by IEEE SMC Hiroshima Chapter. | |||||||||||
| 主題 | ||||||||||||
| 主題Scheme | NDC | |||||||||||
| 主題 | 500 | |||||||||||
| 内容記述 | ||||||||||||
| 内容記述 | Traditional classification algorithms, in many times, perform poorly on imbalanced data sets in which some classes are heavily outnumbered by the remaining classes. For this kind of data, minority class instances, which are usually much more of interest, are often misclassified. The paper proposes a method to deal with them by changing class distribution through oversampling at the borderline between the minority class and the majority class of the data set. A Support Vector Machines (SVMs) classifier then is trained to predict new unknown instances. Compared to other over-sampling methods, the proposed method focuses only on the minority class instances lying around the borderline due to the fact that this area is most crucial for establishing the decision boundary. Furthermore, new instances will be generated in such a manner that minority class area will be expanded further toward the side of the majority class at the places where there appear few majority class instances. Experimental results show that the proposed method can achieve better performance than some other over-sampling methods, especially with data sets having low degree of overlap due to its ability of expanding minority class area in such cases. | |||||||||||
| 言語 | en | |||||||||||
| 出版者 | ||||||||||||
| 出版者 | IEEE SMC Hiroshima Chapter | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||||||||
| 資源タイプ | conference paper | |||||||||||
| 出版タイプ | ||||||||||||
| 出版タイプ | VoR | |||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||
| 関連情報 | ||||||||||||
| 識別子タイプ | URI | |||||||||||
| 関連識別子 | http://www.hil.hiroshima-u.ac.jp/iwcia/2009/ | |||||||||||
| 収録物識別子 | ||||||||||||
| 収録物識別子タイプ | ISSN | |||||||||||
| 収録物識別子 | 1883-3977 | |||||||||||
| 開始ページ | ||||||||||||
| 開始ページ | 24 | |||||||||||
| 書誌情報 |
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009 5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009 p. 24-29, 発行日 2009-11 |
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| 旧ID | 28413 | |||||||||||
