Study on Density Peaks Clustering Based on Hierarchical K-Nearest Neighbors

Chunhua Ren, Linfu Sun, Qishi Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Density Peaks Clustering is a novel clustering algorithm, which can find clusters of arbitrary shapes with fast speed. However, it has a few disadvantages, for example, when the data are unevenly distributed, the clustering performance is not good. Therefore, a improved DPC based on hierarchical k-nearest neighbor (HKNN-DPC) algorithm is proposed, which divided k-nearest neighbors into three layers, each layer of data points has different weight, and redesigned the local density calculation approach. We adopt the proposed algorithm to compare with DPC, DBSCAN and K-means in synthesized and UCI data sets. The experimental results indicated HKNN-DPC had better performance.

Original languageEnglish (US)
Title of host publicationProceedings of IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2019
EditorsLi Zou, Lingling Fang, Bo Fu, Panpan Niu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages664-668
Number of pages5
ISBN (Electronic)9781728123486
DOIs
StatePublished - Nov 2019
Externally publishedYes
Event14th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2019 - Dalian, China
Duration: Nov 14 2019Nov 16 2019

Publication series

NameProceedings of IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2019

Conference

Conference14th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2019
Country/TerritoryChina
CityDalian
Period11/14/1911/16/19

All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems
  • Decision Sciences (miscellaneous)
  • Health Informatics

Keywords

  • density peaks clustering
  • hierarchical k-nearest neighbors
  • local density
  • uneven density distribution

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