A Novel Density Peaks Clustering Algorithm Based on Local Reachability Density

被引：0
|
作者：
Hanqing Wang
Bin Zhou
Jianyong Zhang
Ruixue Cheng
机构：
[1] Southeast University,School of Energy and Environment
[2] Teesside University,School of Computing, Engineering and Digital Technologies
来源：
International Journal of Computational Intelligence Systems | 2020年 / 13卷
关键词：
Clustering algorithm; Density peaks clustering; Local reachability density; Domino effect;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A novel clustering algorithm named local reachability density peaks clustering (LRDPC) which uses local reachability density to improve the performance of the density peaks clustering algorithm (DPC) is proposed in this paper. This algorithm enhances robustness by removing the cutoff distance dc which is a sensitive parameter from the DPC. In addition, a new allocation strategy is developed to eliminate the domino effect, which often occurs in DPC. The experimental results confirm that this algorithm is feasible and effective.
引用
收藏
页码：690 / 697
页数：7
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