关键词: 聚类, 谱聚类, k-调和平均, 初始化

Abstract: Spectral clustering is used in pattern recognition extensively as a novel clustering algorithm in recent years.Due to the initialization dependence of original spectral clustering，this paper introduces the initialization insensitive k-harmonic means algorithm and proposes an initialization independent spectral clustering algorithm.Experiment on the artificial data set and the real data set shows that the improved algorithm has the remarkable enhancement in the stability and the clustering performance compared with traditional k-means algorithm，FCM algorithm and EM algorithm.

Key words: clustering, spectral clustering, k-harmonic means, initialization