Density Peak Clustering Based on Global Density
Min Li, William Zhu · 2023
Density peaks clustering is an efficient clustering method. It regards density peaks determined by local density which depends on cutoff distance as cluster centers to recognize clusters. However, it is difficult to find the appropriate cutoff distance to accurately measure local density. In this paper, we define global density to solve above problem. In order to define the global density of a point, we define the density between any two points. The global density of a point is defined as the sum of the densities from a point to other points. We apply our global density to the density peaks clustering and then propose a new clustering method. Experiments illustrate the effectiveness of our new method.