2023/03/07 by Jiang Xie, Xie, Jiang, Qiao Deng +9
Computer Science · Social Sciences · #Advanced Clustering Algorithms Research #Advanced Computing and Algorithms #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Text and Document Classification Technologies
paper · pdf · doi:10.48550/arxiv.2303.03590
openalex publication_date 2023/03/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In recent years, the problem of fuzzy clustering has been widely concerned. The membership iteration of existing methods is mostly considered globally, which has considerable problems in noisy environments, and iterative calculations for clusters with a large number of different sample sizes are not accurate and efficient. In this paper, starting from the strategy of large-scale priority, the data is fuzzy iterated using granular-balls, and the membership degree of data only considers the two granular-balls where it is located, thus improving the efficiency of iteration. The formed fuzzy granular-balls set can use more processing methods in the face of different data scenarios, which enhances the practicability of fuzzy clustering calculations.