Abstract
Clustering is a method of data analysis. Rough k-means (RKM) by Lingras et al. is one of rough clustering algorithms [3]. The method does not have a clear indicator to determine the most appropriate result because it is not based on objective function. Therefore we proposed a rough clustering algorithm based on optimization of an objective function [7]. This paper will propose a new rough clustering algorithm based on optimization of an objective function with fuzzy-set representation to obtain better lower approximation, and estimate the effectiveness through some numerical examples.
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Onishi, K., Kinoshita, N., Endo, Y. (2014). A Note on Objective-Based Rough Clustering with Fuzzy-Set Representation. In: Torra, V., Narukawa, Y., Endo, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2014. Lecture Notes in Computer Science(), vol 8825. Springer, Cham. https://doi.org/10.1007/978-3-319-12054-6_11
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DOI: https://doi.org/10.1007/978-3-319-12054-6_11
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12053-9
Online ISBN: 978-3-319-12054-6
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