关键词: 聚类融合, 聚类成员选择, 聚类成员加权

Abstract: Traditional clustering fusion method is to integrate all obtained cluster members, it doesn’t eliminate the inferior quality’ influence in  the integration completely, but it can have better advantages in theory from the selection and weight of clustering members to make clustering fusion, which select cluster members through fusioning any two clustering members instead of all clustering members once, and weight cluster members through the method of attribute weighting. It does experiment in the real and simulated datas. The result shows that the clustering algorithm can effectively deal with the difference of members quality, compared to the traditional clustering fusion method, it can get better results and have a good expansibility.

Key words: cluster fusion, cluster member selection, cluster member weighting