2018/01/21 by Waleed Alomoush, Alomoush, Waleed, Ayat Alrosan +1
Computer Science · #Advanced Clustering Algorithms Research #Data Management and Algorithms #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural and Evolutionary Computing (cs.NE) #Text and Document Classification Technologies
paper · pdf · doi:10.48550/arxiv.1802.08729
openalex publication_date 2018/01/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Fuzzy clustering is a famous unsupervised learning method used to collecting similar data elements within cluster according to some similarity measurement. But, clustering algorithms suffer from some drawbacks. Among the main weakness including, selecting the initial cluster centres and the appropriate clusters number is normally unknown. These weaknesses are considered the most challenging tasks in clustering algorithms. This paper introduces a comprehensive review of metahueristic search to solve fuzzy clustering algorithms problems.