| 来源类型 | Article
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| 规范类型 | 其他
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| DOI | 10.1007/s00500-012-0904-7
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| On semi-supervised fuzzy c-means clustering for data with clusterwise tolerance by opposite criteria. |
| Hamasuna Y; Endo Y
|
| 发表日期 | 2013
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| 出处 | Soft Computing 17 (1): 71-81
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| 出版年 | 2013
|
| 语种 | 英语
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| 摘要 | This paper presents a new semi-supervised fuzzy c-means clustering for data with clusterwise tolerance by opposite criteria. In semi-supervised clustering, pairwise constraints, that is, must-link and cannot-link, are frequently used in order to improve clustering performances. From the viewpoint of handling pairwise constraints, a new semi-supervised fuzzy c-means clustering is proposed by introducing clusterwise tolerance-based pairwise constraints. First, a concept of clusterwise tolerance-based pairwise constraints is introduced. Second, the optimization problems of the proposed method are formulated. Especially, must-link and cannot-link are handled by opposite criteria in our proposed method. Third, a new clustering algorithm is constructed based on the above discussions. Finally, the effectiveness of the proposed algorithm is verified through numerical examples. |
| 主题 | Advanced Systems Analysis (ASA)
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| 关键词 | Clusterwise tolerance
Fuzzy c-means clustering
Pairwise constraints
Semi-supervised clustering
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| URL | http://pure.iiasa.ac.at/id/eprint/10541/
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| 来源智库 | International Institute for Applied Systems Analysis (Austria)
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| 引用统计 |
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| 资源类型 | 智库出版物
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| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/129844
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推荐引用方式
GB/T 7714 |
Hamasuna Y,Endo Y. On semi-supervised fuzzy c-means clustering for data with clusterwise tolerance by opposite criteria.. 2013.
|
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