Fuzzy kernel clustering self-adaptive algorithm

Kan Li; Yu Shu Liu

Fuzzy kernel clustering self-adaptive algorithm

Kan Li^*
, Yu Shu Liu

^*此作品的通讯作者

计算机学院

Beijing Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

4 引用（Scopus）

摘要

Kernel function and validity measure function are introduced to the fuzzy clustering algorithm, and fuzzy kernel clustering self-adaptive algorithm is proposed. The algorithm owns better performance than classical clustering algorithms. Experiment results show the feasibility and effectiveness of the fuzzy kernel clustering self-adaptive algorithm.

源语言	英语
页（从-至）	595-597
页数	3
期刊	Kongzhi yu Juece/Control and Decision
卷	19
期	5
出版状态	已出版 - 5月 2004

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title = "Fuzzy kernel clustering self-adaptive algorithm",

abstract = "Kernel function and validity measure function are introduced to the fuzzy clustering algorithm, and fuzzy kernel clustering self-adaptive algorithm is proposed. The algorithm owns better performance than classical clustering algorithms. Experiment results show the feasibility and effectiveness of the fuzzy kernel clustering self-adaptive algorithm.",

keywords = "Feature space, Fuzzy C-means, Mercer kernel, Validity measure function",

author = "Kan Li and Liu, \{Yu Shu\}",

year = "2004",

month = may,

language = "English",

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pages = "595--597",

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AU - Liu, Yu Shu

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AB - Kernel function and validity measure function are introduced to the fuzzy clustering algorithm, and fuzzy kernel clustering self-adaptive algorithm is proposed. The algorithm owns better performance than classical clustering algorithms. Experiment results show the feasibility and effectiveness of the fuzzy kernel clustering self-adaptive algorithm.

KW - Feature space

KW - Fuzzy C-means

KW - Mercer kernel

KW - Validity measure function

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M3 - Article

AN - SCOPUS:3442877646

SN - 1001-0920

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JO - Kongzhi yu Juece/Control and Decision

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Fuzzy kernel clustering self-adaptive algorithm

摘要

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