Abstract:

Clustering is a major research orientation in data mining．Considering the drawbacks of the existing clustering algorithm, a new similarity measure is proposed firstly. Then the discernibility ability of the rough set theory is used to measure the importance of attributes, and thus a weighted rough clustering algorithm based on new similarity measure is proposed. Finally，we test our algorithm versus other algorithms on the UCI datasets, and the experimental results show the proposed clustering algorithm can deal with the categorical data, and does not need to be given the number of cluster, and especially, it improves the cluster quality.

Key words: clustering analysis;rough set;similarity;data mining