An optimal and stable algorithm for clustering numerical data

In the conventional k-means framework, seeding is the first step toward optimization before the objects are clustered. In random seeding, two main issues arise: the clustering results may be less than optimal and different clustering results may be obtained for every run. In real-world applications,...

詳細記述

書誌詳細
出版年:Algorithms
第一著者: Seman A.; Sapawi A.M.
フォーマット: 論文
言語:English
出版事項: MDPI AG 2021
オンライン・アクセス:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109399419&doi=10.3390%2fa14070197&partnerID=40&md5=28e9e298aa7e11e0021cdaf07826ebad