A kernel clustering algorithm based on diameters
| Autor: | Costa, Miguel Ângelo Peixoto, Rocha, Ana Maria A. C., Fernandes, Edite Manuela da G. P. |
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| Přispěvatelé: | Universidade do Minho |
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Popis: | This paper analyzes an iterative kernel partitioning clustering algorithm that dynamically merges, removes and adds clusters using some characteristics, like the radii and diameters of the clusters, and distance between centers. The clustering is carried out in feature space in terms of a kernel function so that non-linearly separable clusters are identified. The preliminary experiments with seven datasets show that the proposed algorithm is able to successfully converge to the expected clustering. It is also shown that the algorithm performance is sensitive to the parameter σ of the Gaussian kernel. This work has been supported by FCT – Funda¸c˜ao para a Ciˆencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020, UIDB/00013/2020 and UIDP/00013/2020 of CMAT-UM |
| Databáze: | OpenAIRE |
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