关键词: 聚类, 数据竞争, 聚合场, 密度不均匀

Abstract: Since the existing data competition clustering algorithm has poor performance on density inhomogeneous datasets, this paper proposes a density adaptive data competition clustering algorithm. Firstly, a local density adaptive line is defined. Nextly, the density adaptive similarity can be calculated based on local density adaptive line. The density adaptive similarity can reflect the global data space distribution information and local information of data points, which can describe the relationship between data points more effectively. Then, the density adaptive similarity is used in data competition clustering algorithm. The simulation results on synthetic and real life datasets show that the proposed algorithm can obtain better performance on density inhomogeneous datasets than existing data competition clustering algorithm.

Key words: clustering, data competition, aggregation field, density inhomogeneous