McDPC: Multi‐center density peak clustering

• Main Authors: WANG, Yizhang, WANG, Di, ZHANG, Xiaofeng, PANG, Wei, MIAO, Chunyan, TAN, Ah-hwee, ZHOU, You
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Density peak clustering; Multi-center cluster; Image segmentation; Databases and Information Systems; Programming Languages and Compilers; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/5186; https://ink.library.smu.edu.sg/context/sis_research/article/6189/viewcontent/NCAA2020.pdf
• Institution: Singapore Management University

Density peak clustering (DPC) is a recently developed density-based clustering algorithm that achieves competitive performance in a non-iterative manner. DPC is capable of effectively handling clusters with single density peak (single center), i.e., based on DPC’s hypothesis, one and only one data p...