Feature Selection and Semisupervised Fuzzy Clustering

被引：1

作者：

Kong, Yi-qing ^{[1
]}

Wang, Shi-tong ^{[1
]}

机构：

[1] Jiangnan Univ, Sch Informat Technol, Wuxi 214122, Peoples R China

来源：

FUZZY INFORMATION AND ENGINEERING | 2009年 / 1卷 / 02期

关键词：

Semisupervised clustering; Feature selection;

D O I：

10.1007/s12543-009-0014-0

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Semisupervised fuzzy clustering plays an important role in discovering structure in data set with both labelled and unlabelled data. The proposed method learns the task of classification and feature selection through the generalized form of Fuzzy C-means. Experimental results illustrate appropriate feature selection and classification accuracy with both synthetic and benchmark data sets.

引用

页码：179 / 190

页数：12

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