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Study on multi-center fuzzy C-means algorithm based on transitive closure and spectral clustering

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成果类型:
期刊论文
作者:
Zeng, Shan*;Tong, Xiaojun;Sang, Nong
通讯作者:
Zeng, Shan
作者机构:
[Zeng, Shan] Wuhan Polytech Univ, Coll Math & Comp Sci, Wuhan 430023, Hubei, Peoples R China.
[Tong, Xiaojun] Wuhan Text Univ, Coll Math & Comp Sci, Wuhan 430077, Hubei, Peoples R China.
[Sang, Nong] Huazhong Univ Sci & Technol, Inst Pattern Recognit & Artificial Intelligence, Wuhan 430074, Hubei, Peoples R China.
通讯机构:
[Zeng, Shan] W
Wuhan Polytech Univ, Coll Math & Comp Sci, Wuhan 430023, Hubei, Peoples R China.
语种:
英文
关键词:
Fuzzy C-means algorithm;Lattice similarity;Multi-center;Spectral clustering
期刊:
Applied Soft Computing
ISSN:
1568-4946
年:
2014
卷:
16
页码:
89-101
基金类别:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61303116, 61072143]
机构署名:
本校为第一且通讯机构
院系归属:
数学与计算机学院
摘要:
Fuzzy C-means (FCM) clustering has been widely used successfully in many real-world applications. However, the FCM algorithm is sensitive to the initial prototypes, and it cannot handle non-traditional curved clusters. In this paper, a multi-center fuzzy C-means algorithm based on transitive closure and spectral clustering (MFCM-TCSC) is provided. In this algorithm, the initial guesses of the locations of the cluster centers or the membership values are not necessary. Multi-centers are adopted to represent the non-spherical shape of clusters. T...

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