| Mercer Kernel Based Fuzzy Clustering Self-Adaptive Algorithm |
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| 作者姓名： | 李侃 刘玉树 |
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| 作者单位： | SchoolofInformationScienceandTechnology,BeijingInstituteofTechnology,Beijing100081,China |
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| 基金项目： | SponsoredbytheMinisterialLevelAdvancedResearchFoundation(4010503) |
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| 摘 要： | A novel mercer kernel based fuzzy clustering self-adaptive algorithm is presented. The mercer kernel method is introduced to the fuzzy c-means clustering. It may map implicitly the input data into the high-dimensional feature space through the nonlinear transformation. Among other fuzzy c-means and its variants, the number of clusters is first determined. A self-adaptive algorithm is proposed. The number of clusters, which is not given in advance, can be gotten automatically by a validity measure function. Finally, experiments are given to show better performance with the method of kernel based fuzzy c-means self-adaptive algorithm.
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| 关 键 词： | 模糊分析 聚类分析 自适应法则 运算法则 人工智能 |
| 收稿时间： | 2003/9/15 0:00:00 |
Mercer Kernel Based Fuzzy Clustering Self-Adaptive Algorithm |
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| LI Kan and LIU Yu-shu.Mercer Kernel Based Fuzzy Clustering Self-Adaptive Algorithm[J].Journal of Beijing Institute of Technology,2004,13(4):351-354. |
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| Authors: | LI Kan and LIU Yu-shu |
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| Affiliation: | School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China |
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| Abstract: | A novel mercer kernel based fuzzy clustering self-adaptive algorithm is presented. The mercer kernel method is introduced to the fuzzy c-means clustering. It may map implicitly the input data into the high-dimensional feature space through the nonlinear transformation. Among other fuzzy c-means and its variants, the number of clusters is first determined. A self-adaptive algorithm is proposed. The number of clusters, which is not given in advance, can be gotten automatically by a validity measure function. Finally, experiments are given to show better performance with the method of kernel based fuzzy c-means self-adaptive algorithm. |
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| Keywords: | fuzzy c-means mercer kernel feature space validity measure function |
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