Comparative density peaks clustering

作者：

Highlights：

• The proposed method significantly outperforms the original Density Peaks algorithm.

• We analyze of the Density Peaks algorithm from the perspective of tree structure.

• Using the novel comparative quantity models the assumptions quantitatively.

摘要

•The proposed method significantly outperforms the original Density Peaks algorithm.•We analyze of the Density Peaks algorithm from the perspective of tree structure.•Using the novel comparative quantity models the assumptions quantitatively.

论文关键词：Clustering,Density peaks clustering,Geodesic distance,Density-based clustering

论文评审过程：Received 12 June 2017, Revised 25 October 2017, Accepted 9 November 2017, Available online 10 November 2017, Version of Record 14 December 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.11.020