Abstract
This paper establishes a new metric space for the clustering problems. The neighbors on the object set induced by the topology molecular lattice on ∗ EI algebra are given and a new distance based on the neighbors is proposed. In the proposed clustering algorithm, the Euclidean metric is replaced by the new distance based on the order relationship of the samples on the attributes. As a result, using the method to Iris data we show it has a better result and clearer classification than the other clustering algorithm based on the Euclidean metric. This study shows that the AFS topology fuzzy clustering algorithm can obtain an high clustering accuracy according to order relationship.
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Ding, R., Liu, X., Chen, Y. (2006). The Fuzzy Clustering Algorithm Based on AFS Topology. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_11
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DOI: https://doi.org/10.1007/11881599_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45916-3
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