关键词: 类簇中心, 数据场, 聚类, 孤立点

Abstract: In view of the existing clustering algorithms with widespread low clustering quality, parameter dependency and outlier effects obvious, in this paper, a clustering method based on the field data is proposed. The algorithm has its basis in the assumptions that cluster centers are surrounded by neighbors with lower local potential and that they are at a relatively large distance from any points with a higher local potential. According to the characteristics that the potential value of isolated point is equal to zero, remove the outlier and finally the other object points are divided into larger than its potential value and nearest neighbor type of clusters, so as to achieve clustering. Simulation results show that the proposed algorithm is effective and has no effect on the shape of the data set, and it can find out clusters center and outliers accurately without artificial parameters.

Key words: cluster center, data field, clustering, outlier