| Novel Cluster Validity Index for FCM Algorithm |
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| 作者姓名： | Jian Yu and Cui-Xia Li |
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| 作者单位： | Institute of Computer Science, Beijing Jiaotong University, Beijing 100044, P.R. China |
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| 基金项目： | Supported by the National Natural Science Foundation of China under Grant No. 60303014, |
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| 摘 要： | How to determine an appropriate number of clusters is very important when implementing a specific clustering algorithm, like c-means, fuzzy c-means （FCM）. In the literature, most cluster validity indices are originated from partition or geometrical property of the data set. In this paper, the authors developed a novel cluster validity index for FCM, based on the optimality test of FCM. Unlike the previous cluster validity indices, this novel cluster validity index is inherent in FCM itself. Comparison experiments show that the stability index can be used as cluster validity index for the fuzzy c-means.
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| 关 键 词： | 聚类有效性 最优性测试 FCM算法 聚类算法 |
| 收稿时间： | 2004-09-25 |
| 修稿时间： | 2004-09-252005-06-20 |
Novel Cluster Validity Index for FCM Algorithm |
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| Jian Yu and Cui-Xia Li.Novel Cluster Validity Index for FCM Algorithm[J].Journal of Computer Science and Technology,2006,21(1):137-140. |
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| Authors: | Jian Yu Cui-Xia Li |
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| Affiliation: | (1) Institute of Computer Science, Beijing Jiaotong University, Beijing, 100044, P.R. China |
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| Abstract: | How to determine an appropriate number of clusters is very important when implementing a specific clustering algorithm, like c-means, fuzzy c-means (FCM). In the literature, most cluster validity indices are originated from partition or geometrical property of the data set. In this paper, the authors developed a novel cluster validity index for FCM, based on the optimality test of FCM. Unlike the previous cluster validity indices, this novel cluster validity index is inherent in FCM itself. Comparison experiments show that the stability index can be used as cluster validity index for the fuzzy c-means. |
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| Keywords: | cluster validity optimality test FCM |
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