An Effective Compound Clustering Algorithm

摘要：

There usually exit some reactive and redundant attributes in clustering objects. In order to improve the efficiency and veracity of clustering, we must delete those reactive and redundant attributes before clustering. A compound clustering algorithm is proposed in this paper. The algorithm first introduces fuzzy clustering to classify attributes, and then uses Fuzzy C-means (FCM) algorithm to pariition objects and verify which attributes are redundant. The effectiveness of the proposed compound clustering algorithm is demonstrated with the Fisher Iris data set.

作者: Jianlin Zhang Wensheng Zou Jianfeng Xu Lan Liu

作者单位: Nanchang University, Nanchang 330047, PR China

会议类型: 国际会议

会议名称: The Second International Joint Conference on Computational Science and Optimization(CSO 2009)(2009 国际计算科学与优化会议)

会议地点: 三亚

会议语种:英文

页码: 1423-1426

在线出版日期: 2009-04-24（万方平台首次上网日期，不代表论文的发表时间）