数据质量聚类算法

The clustering center has a great effect on the clustering result. In this paper, a new concept of the data mass is proposed. The mass of data represents one of the inherent attributes of the data. With different view angles of data mining, the data mass maybe different. Based on the concept of data mass, a new clustering algorithm, which is clustering data with mass, is put forward. This new algorithm finds the clustering centers based on two attributes of data: the data mass and the data distance. And it can complete the clustering process with only one pass of the whole dataset. Experimental results show that the proposed algorithm can find the clustering center accurately and can get better clustering result than the same typical clustering algorithms, such as K-means, K-medoids and clustering by fast search and find of density peaks.