Abstract
In this paper, the q-divergence-regularized Bezdek-type fuzzy clustering approach is proposed for categorical multivariate data. Because the approach proposed here reduces to the conventional methods via appropriate control of the fuzzification parameters, it is considered as a generalization. Further, numerical experiments were conducted to show that the proposed method outperformed the conventional method in terms of clustering accuracy.
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Kanzawa, Y. (2021). q-Divergence Regularization of Bezdek-Type Fuzzy Clustering for Categorical Multivariate Data. In: Torra, V., Narukawa, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2021. Lecture Notes in Computer Science(), vol 12898. Springer, Cham. https://doi.org/10.1007/978-3-030-85529-1_18
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DOI: https://doi.org/10.1007/978-3-030-85529-1_18
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