Surono, Sugiyarto and Haryati, Annisa Eka and Eliyanto, Joko An Optimization of Several Distance Function on Fuzzy Subtractive Clustering. In: Fuzzy Systems and Data Mining VII. IOS Press Ebooks, pp. 329-338.
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Abstract
Fuzzy Subtractive Clustering (FSC) is a technique of fuzzy clustering where the cluster to be formed is unknown. The distance function in the FSC method has an important role in determining the number of points that have the most neighbors. Therefore, this study uses several distance functions. The results obtained indicate that the DBI results indicate that the Euclidean distance has a good cluster evaluation result in the number of clusters 4. Meanwhile, for the PC value the combination of the Minkowski Chebysev distance produces a good PC value in the number of clusters 2.
| Item Type: | Book Section |
|---|---|
| Keyword: | Fuzzy subtractive clustering, partition coefficient, avies ouldin index |
| Subjects: | Q Science > QA Mathematics |
| Depositing User: | Dr Sugiyarto Surono |
| Date Deposited: | 22 Nov 2022 07:05 |
| Last Modified: | 22 Nov 2022 07:05 |
| URI: | http://eprints.uad.ac.id/id/eprint/37574 |
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