计算机工程与应用Issue(17)：142-145,190,5.DOI:10.3778/j.issn.1002-8331.1210-0203
改进的粗糙模糊和模糊粗糙K-均值聚类算法
Improvement of rough fuzzy and fuzzy rough clustering algorithm
摘要
Abstract
The shortcomings of the original clustering methods are analyzed. Moreover, the rough theory and fuzzy theory are combined together. The improvement of rough fuzzy K-means clustering algorithm is given. A fuzzy rough K-means clustering algorithm is designed, and the validity of fuzzy rough K-means clustering algorithm is verified. The proposed clustering algorithms are applied to support vector machine. In the above applications, the training samples are pre-processed to reduce the number of samples and improve the training speed and the classification accuracy.关键词
粗糙模糊K-均值聚类/模糊粗糙K-均值聚类/支持向量机Key words
rough fuzzy K-mean clustering/fuzzy rough K-mean clustering/support vector machine分类
信息技术与安全科学引用本文复制引用
田大增,吴静..改进的粗糙模糊和模糊粗糙K-均值聚类算法[J].计算机工程与应用,2014,(17):142-145,190,5.基金项目
国家自然科学基金（No.61073121）；河北省自然科学基金（No.A2012201033，No.F2012402037）；河北省教育厅自然科学青年基金（No.Q2012046）。 （）
