This paper presents a multistage random sampling fuzzy c-means-based clustering algorithm, which significantly reduces the computation time required to partition a data set into c classes. A series of subsets of the full data set are used to create initial cluster centers in order to provide an appr
β¦ LIBER β¦
D-fuzzy clustering
β Scribed by Kaoru Hirota; Witold Pedrycz
- Publisher
- Elsevier Science
- Year
- 1995
- Tongue
- English
- Weight
- 524 KB
- Volume
- 16
- Category
- Article
- ISSN
- 0167-8655
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Fuzzy clustering algorithms are a basic tool for cluster analysis. Among these. the geometrical fuzzy clustering algorithms arc used when the clustering problem can he viewed as trying to find linear or ellipsoidal concentrations in data. This paper provides a theoretical framework in which currentl