Abstract: The scale of original data is very large.It is difficult to realize the clustering algorithm.Clustering analysis often takes the key attributes as classification parameters.This paper presents a method of clustering analysis based on attributes reduction.It can reduce the redundant attributes，and improve the robusting and efficiency of clustering analysis.

摘要： 由于原始海量数据规模较大，聚类算法难以实现，而且聚类分析有时候只考虑关键属性作为分类参数。因此提出了一种对原始数据先进行属性约简，再聚类分析的策略，可以在一定程度上消除数据对象中的冗余属性，改善聚类分析的鲁棒性，提高聚类算法的有效性。