Interval Type-2 Fuzzy C-Means Approach to Collaborative Clustering

被引：0
|
作者：
Trong Hop Dang [1 ,2 ]
Long Thanh Ngo [1 ]
Pedrycz, Witold [3 ]
机构：
[1] Le Quy Don Tech Univ, Dept Informat Syst, 236 Hoang Quoc Viet, Hanoi, Vietnam
[2] Hanoi Univ Ind, Ctr Informat Technol, Hanoi, Vietnam
[3] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6R 2V4, Canada
来源：
2015 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2015) | 2015年
关键词：
Fuzzy clustering; Collaborative Clustering; Fuzzy C-Means; Type-2 Fuzzy Sets; Cluster Validity Measures; SETS;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
There have been numerous studies on using the FCM algorithm in clustering and collaboration clustering, especially in data analysis, data mining and pattern recognition. In this study, we present new methods involving interval Type-2 fuzzy sets to realize collaborative clustering. Data in which the clustering results realized at one data site impact clustering carried out at other data sites. Those methods endowed with interval type-2 fuzzy sets help cope with uncertainties present in data. The experiment with weather data sets has shown better results in comparison with the previous approaches.
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页数：7
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