关键词: K-均值算法, 密度, 聚类中心

Abstract: Considering the disadvantage of dimension ruin and original clustering centers difficult to solve,this paper proposes an improving K-means clustering algorithm,which core is to improve traditional algorithm by lowering dimensions and searching based on density and diffused original clustering centers.The results of the experiment show that this algorithm can obtain better clustering result than traditional K-means clustering algorithm at clustering precision and stability.

Key words: K-means clustering algorithm, density, clustering centers