基于证据理论的三向密度峰值聚类OA北大核心CSTPCD

In order to avoid the error propagation of clustering labels and fully mine the neighborhood information,a three-way density peak clustering method based on evidence theory is proposed.The clustering information of k-nearest neighbor was considered when non grouping points were allocated,which was conducive to improving the clustering accuracy.The evidence theory was used to describe and combine these neighbor information,so that the established three-way clustering model could assign them to the most likely clusters,thus effectively avoiding the propagation of wrong labels in the peak density clustering algorithm.Experimental results on several data sets show that the proposed method can effectively avoid the error propagation of clustering labels and achieve high clustering accuracy.