Abstract
In this paper, we describe fuzzy agglomerative clustering, a brand new fuzzy clustering algorithm. The basic idea of the proposed algorithm is based on the well-known hierarchical clustering methods. To achieve the soft or fuzzy output of the hierarchical clustering, we combine the single-linkage and complete-linkage strategy together with a fuzzy distance. As the algorithm was created recently, we cover only some basic experiments on synthetic data to show some properties of the algorithm. The reference implementation is freely available.
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Konkol, M. (2015). Fuzzy Agglomerative Clustering. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9119. Springer, Cham. https://doi.org/10.1007/978-3-319-19324-3_19
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DOI: https://doi.org/10.1007/978-3-319-19324-3_19
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19323-6
Online ISBN: 978-3-319-19324-3
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