An efficient density-based clustering algorithm with circle-filtering strategy Online publication date: Tue, 08-Dec-2020
by Xiao Xu
International Journal of Collaborative Intelligence (IJCI), Vol. 2, No. 2, 2020
Abstract: Recently a density peaks clustering algorithm (DPC) was proposed to obtain arbitrary shapes of the clusters effectively. The cluster centres are discovered by finding density peaks according to the decision graph which drawn based on the density-distance. However, the computational complexity is extremely high for calculating the density-distance of each point, which limits the application of DPC for the large-scale data sets. To overcome this limitation, an efficient density-based clustering algorithm with circle-filtering strategy (CFC) is proposed. CFC removes useless points based on a circle-filtering strategy first, and then the cluster centres are selected according to the remaining points. Experimental results show that CFC can reduce the computational complexity on the basis of ensuring the accuracy of clustering, and outperforms DPC.
Online publication date: Tue, 08-Dec-2020
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Collaborative Intelligence (IJCI):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com