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Proceedings of the 16th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 25

A Novel Cluster Ensemble based on a Single Clustering Algorithm

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DOI: http://dx.doi.org/10.15439/2021F28

Citation: Proceedings of the 16th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 25, pages 127–135 ()

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Abstract. In recent years, several cluster ensemble methods have been developed, but they still have some limitations. They often use different clustering algorithms in both stages of the clustering ensemble method, such as the ensemble generation step and the consensus function, resulting in a compatibility issues. To deal with it, we propose a novel cluster ensemble method based on an identical clustering algorithm (CEI). Experiments on real-world datasets from various sources show that CEI improves accuracy by 5\% on average compared to state-of-the-art cluster ensemble methods and by 55.54\% compared to AP while consuming 44.60\% less execution time.

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